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gdjCL4vQM6 | https://openreview.net/forum?id=gdjCL4vQM6 | LIGHT: LLM-guided Graph Expert Routing for Semi-supervised Domain Generalization | 3.333333 | 4 | [
4,
4,
2
] | [
3,
5,
4
] | 3 | [
"GNNs",
"OOD Generalization",
"Domain Generalization",
"Semi-supervised Learning",
"LLMs",
"MoE"
] | Although graph neural networks (GNNs) have shown remarkable performance in graph machine learning, their effectiveness in practice often suffers from realistic challenges including distribution shifts and label scarcity. Towards this end, this paper studies the problem of semi-supervised domain generalization, which ai... | unsupervised, self-supervised, semi-supervised, and supervised representation learning | https://openreview.net/pdf?id=gdjCL4vQM6 | 2025-09-19T20:27:14 | 3 | [
{
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"rating": 4,
"confidence": 3,
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"contribution": 3,
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"summary": "This ... | |
6mpv9kG81P | https://openreview.net/forum?id=6mpv9kG81P | Domain-Specific Data Synthesis for LLMs via Minimal Sufficient Representation Learning | 4.666667 | 3.666667 | [
6,
2,
6
] | [
4,
3,
4
] | 3 | [
"synthetic data",
"representation learning"
] | Large Language Models have demonstrated remarkable progress in general-purpose capabilities and can achieve strong performance in specific domains through fine-tuning on domain-specific data. However, acquiring high-quality data for target domains remains a significant challenge. Existing data synthesis approaches foll... | unsupervised, self-supervised, semi-supervised, and supervised representation learning | https://openreview.net/pdf?id=6mpv9kG81P | 2025-09-19T14:15:58 | 3 | [
{
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"reviewer_name": "Reviewer_tYar",
"rating": 6,
"confidence": 4,
"soundness": 3,
"contribution": 3,
"presentation": 3,
"summary": "The p... | |
VJqfoHU4Op | https://openreview.net/forum?id=VJqfoHU4Op | XDex: Learning Cross-Embodiment Dexterous Grasping with 1000 Hands | 4.5 | 3.75 | [
4,
6,
2,
6
] | [
4,
3,
4,
4
] | 4 | [
"Dexterous Grasping",
"Cross-embodiment"
] | Synthesizing dexterous grasps across various hands remains a fundamental challenge in robotic manipulation due to morphology gaps in geometry, topology, and kinematics. We hypothesize that scaling the diversity and number of hand embodiments improves generalization to unseen hands. To this end, we introduce XDex, a fra... | applications to robotics, autonomy, planning | https://openreview.net/pdf?id=VJqfoHU4Op | 2025-09-03T04:55:15 | 4 | [
{
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"reviewer_name": "Reviewer_2jri",
"rating": 4,
"confidence": 4,
"soundness": 3,
"contribution": 2,
"presentation": 3,
"summary": "This p... | |
JbyaS5zhcB | https://openreview.net/forum?id=JbyaS5zhcB | Geo-Invariant Scoring Lead with Domain-Adversarial Transformers | 3.6 | 3 | [
6,
2,
2,
6,
2
] | [
3,
4,
3,
3,
2
] | 5 | [
"domain adaptation",
"transformers",
"lead scoring",
"adversarial learning",
"geographic fairness",
"DANN",
"sequential modeling"
] | Predicting B2B lead conversion requires not only modeling long‑range dependencies in richly sequenced customer interactions but also ensuring fair performance across under‑represented geographies. While our DeepScore transformer backbone improved overall AUPR from $0.266$ to $0.360$, it exhibited significant geo‑skew: ... | We augment transformer-based B2B lead scoring with domain-adversarial training to achieve geography-invariant representations, reducing regional performance gaps by 12.3% without degrading majority-region accuracy. | alignment, fairness, safety, privacy, and societal considerations | https://openreview.net/pdf?id=JbyaS5zhcB | 2025-09-20T05:41:58 | 5 | [
{
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kIT1aA8SbY | https://openreview.net/forum?id=kIT1aA8SbY | Stability in Training PINNs for Stiff PDEs: Why Initial Conditions Matter | 3 | 3.5 | [
2,
6,
2,
2
] | [
3,
3,
4,
4
] | 4 | [
"Physics-Informed Neural Networks",
"Stiff PDEs",
"Hard Constraints",
"Initial Condition",
"Ablation Study",
"Neural Tangent Kernel"
] | Training Physics-Informed Neural Networks (PINNs) on stiff time-dependent PDEs remains highly unstable. Through rigorous ablation studies, we identify a surprisingly critical factor: the enforcement of initial conditions. We present the first systematic ablation of two core strategies, hard initial-condition constrain... | neurosymbolic & hybrid AI systems (physics-informed, logic & formal reasoning, etc.) | https://openreview.net/pdf?id=kIT1aA8SbY | 2025-09-20T05:25:52 | 6 | [
{
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"summary": "This ... | |
s0nYSwlV3I | https://openreview.net/forum?id=s0nYSwlV3I | Influence without Confounding: Causal Discovery from Temporal Data with Long-term Carry-over Effects | 5 | 3.75 | [
8,
2,
4,
6
] | [
4,
4,
3,
4
] | 4 | [
"Causal Discovery",
"Reinforcement Learning",
"QR Decomposition",
"Long-term Carry-over Effects"
] | Learning causal structures from temporal data is fundamental to many practical tasks, such as physical laws discovery and root causes localization.
Real-world systems often exhibit long-term carry-over effects, where the value of a variable at the current time can be influenced by distant past values of other variab... | causal reasoning | https://openreview.net/pdf?id=s0nYSwlV3I | 2025-09-20T00:03:50 | 4 | [
{
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"rating": 8,
"confidence": 4,
"soundness": 4,
"contribution": 4,
"presentation": 3,
"summary": "The p... | |
uikLSN1yot | https://openreview.net/forum?id=uikLSN1yot | The SMeL Test: A simple benchmark for media literacy in language models | 4 | 3.5 | [
2,
4,
8,
2
] | [
3,
4,
4,
3
] | 4 | [
"media literacy",
"benchmark",
"LLM"
] | The internet is rife with unattributed, deliberately misleading, or otherwise untrustworthy content. Though large language models (LLMs) are often tasked with autonomous web browsing, the extent to which they have learned the simple heuristics human researchers use to navigate this noisy environment is not currently kn... | Current language models are incapable of filtering out untrustworthy information in context. | datasets and benchmarks | https://openreview.net/pdf?id=uikLSN1yot | 2025-09-20T03:10:48 | 4 | [
{
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"rating": 2,
"confidence": 3,
"soundness": 2,
"contribution": 1,
"presentation": 2,
"summary": "The w... |
9b6Ox5MVhq | https://openreview.net/forum?id=9b6Ox5MVhq | FewGAD: Few-Shot Enhanced Graph Anomaly Detection via Generative Contrastive Learning | 3 | 4.25 | [
4,
2,
4,
2
] | [
5,
4,
4,
4
] | 4 | [
"Anomaly Detection; Graph Neural Network; Few-shot Learning;"
] | Graph anomaly detection (GAD) is critical in domains such as fraud detection, cybersecurity, and social network monitoring. However, existing approaches face two major challenges: the inherent scarcity of labeled anomalies in practical scenarios, and the widespread reliance on graph augmentation, which often distorts a... | unsupervised, self-supervised, semi-supervised, and supervised representation learning | https://openreview.net/pdf?id=9b6Ox5MVhq | 2025-09-15T14:29:06 | 4 | [
{
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"reviewer_name": "Reviewer_oEJ9",
"rating": 4,
"confidence": 5,
"soundness": 2,
"contribution": 2,
"presentation": 3,
"summary": "This p... | |
kbP98SvPGV | https://openreview.net/forum?id=kbP98SvPGV | Boosting Verifiable Industrial Code Generation by Reliable Task Generation at Scale | 5.5 | 3.25 | [
4,
6,
4,
8
] | [
4,
3,
3,
3
] | 4 | [
"Industrial Control Systems",
"Programmable Logic Controllers",
"Data Augmentation",
"Code Generation"
] | Recent advances in industrial copilots (e.g., from Siemens, Rockwell and Schneider) for Programmable Logic Controllers (PLCs) have the potential to transform the way control engineers program. However, the closed-source nature and scarcity of data for Industrial Control System (ICS) programming tasks cast fundamental c... | datasets and benchmarks | https://openreview.net/pdf?id=kbP98SvPGV | 2025-09-19T11:51:31 | 4 | [
{
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"rating": 4,
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"soundness": 3,
"contribution": 2,
"presentation": 3,
"summary": "This ... | |
APCJj5r6Os | https://openreview.net/forum?id=APCJj5r6Os | A Computationally Efficient Case-Control Sampling Framework for G-Formula with Longitudinal Data | 2.666667 | 3.333333 | [
2,
4,
2
] | [
3,
3,
4
] | 3 | [
"Causal inference",
"time-varying treatment",
"survival analysis",
"rare outcomes",
"case-control sampling"
] | Estimating the causal effect of time-varying treatments on survival outcomes in large observational studies is computationally demanding, particularly when outcomes are rare. The iterative conditional expectation (ICE) estimator within the g-formula framework is effective but becomes computationally burdensome when boo... | We propose a case-control enhanced g-formula approach to efficiently estimate causal effects of time-varying treatments on rare survival outcomes. | causal reasoning | https://openreview.net/pdf?id=APCJj5r6Os | 2025-09-20T08:00:10 | 3 | [
{
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"rating": 2,
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"contribution": 1,
"presentation": 1,
"summary": "The a... |
Ard2QzPAUK | https://openreview.net/forum?id=Ard2QzPAUK | BeliefFormer: Belief Attention in Transformer | 3.5 | 3 | [
4,
4,
4,
2
] | [
3,
3,
2,
4
] | 4 | [
"Transformer; orthogonal projection; BeliefFormer"
] | In this paper, we consider modifying the attention layer in Transformer to improve its generalization performance. Conceptually speaking, the standard attention layer takes the softmax-based weighted summation of V vectors as the residual signal (with a linear mapping for dimensionality alignment) when performing the s... | incorporating orthogonal projection as residual signals into attention layer in Transformer to improve generation performance | foundation or frontier models, including LLMs | https://openreview.net/pdf?id=Ard2QzPAUK | 2025-09-20T18:38:56 | 4 | [
{
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"reviewer_id": "ICLR.cc/2026/Conference/Submission25156/Reviewer_XiS7",
"reviewer_name": "Reviewer_XiS7",
"rating": 4,
"confidence": 3,
"soundness": 2,
"contribution": 2,
"presentation": 3,
"summary": "This ... |
LnbMSnQpXb | https://openreview.net/forum?id=LnbMSnQpXb | ADDI: A Simplified E2E Autonomous Driving Model with Distinct Experts and Implicit Interactions | 2 | 4.25 | [
2,
2,
2,
2
] | [
4,
4,
5,
4
] | 4 | [
"CV",
"Imitation Learning",
"Applications",
"3D vision"
] | End-to-end autonomous driving has emerged as a promising research trend aimed at achieving autonomy from a human-like driving perspective. Traditional solutions often divide the task into four sub-tasks—tracking-by-detection, online mapping, prediction, and planning—with several interactions to polish planning. However... | A simple and efficient end-to-end autonomous driving method. | applications to robotics, autonomy, planning | https://openreview.net/pdf?id=LnbMSnQpXb | 2025-09-05T17:09:05 | 5 | [
{
"id": "49gRGFrckE",
"forum": "LnbMSnQpXb",
"review_number": 4,
"reviewer_id": "ICLR.cc/2026/Conference/Submission2357/Reviewer_s69D",
"reviewer_name": "Reviewer_s69D",
"rating": 2,
"confidence": 4,
"soundness": 2,
"contribution": 2,
"presentation": 2,
"summary": "This p... |
0wCTDqkK8I | https://openreview.net/forum?id=0wCTDqkK8I | Quantization with Purpose: Loss-Aware Bit Allocation for Gradient Compression | 4.5 | 3.25 | [
2,
8,
4,
4
] | [
4,
3,
2,
4
] | 4 | [
"Gradient Compression",
"Rate-Distortion Optimization",
"Bit Allocation",
"Quantization"
] | Gradient quantization is a critical technique for reducing communication overhead in large-scale distributed training. However, existing methods often employ fixed bit-width quantization or adaptive quantizers optimized with signal-level distortion metrics such as MSE, which poorly correlate with model performance. In ... | optimization | https://openreview.net/pdf?id=0wCTDqkK8I | 2025-09-19T16:55:30 | 4 | [
{
"id": "7E4NGBn0h8",
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"reviewer_id": "ICLR.cc/2026/Conference/Submission17101/Reviewer_xQTq",
"reviewer_name": "Reviewer_xQTq",
"rating": 2,
"confidence": 4,
"soundness": 2,
"contribution": 2,
"presentation": 3,
"summary": "The a... | |
rpPtgMC5s9 | https://openreview.net/forum?id=rpPtgMC5s9 | Relational Transformer: Toward Zero-Shot Foundation Models for Relational Data | 6 | 3.666667 | [
6,
6,
6
] | [
5,
3,
3
] | 3 | [
"foundation models",
"relational deep learning",
"relational data",
"transformer"
] | Pretrained transformers readily adapt to new sequence modeling tasks via zero-shot prompting, but relational domains still lack architectures that transfer across datasets and tasks.
The core challenge is the diversity of relational data, with varying heterogeneous schemas, graph structures, and functional dependencies... | A novel architecture for relational data that shows strong zero-shot abilities on unseen datasets after pre-training. | foundation or frontier models, including LLMs | https://openreview.net/pdf?id=rpPtgMC5s9 | 2025-09-18T04:59:54 | 3 | [
{
"id": "UdREXkie1B",
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"reviewer_id": "ICLR.cc/2026/Conference/Submission9833/Reviewer_fWfy",
"reviewer_name": "Reviewer_fWfy",
"rating": 6,
"confidence": 5,
"soundness": 3,
"contribution": 3,
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"summary": "This p... |
IRrQgf2GAl | https://openreview.net/forum?id=IRrQgf2GAl | Query-Kontext: An Unified Multimodal Model for Image Generation and Editing | 5 | 3.75 | [
4,
4,
6,
6
] | [
4,
4,
4,
3
] | 4 | [
"Diffusion model",
"VLM",
"Image Generation",
"Image Editing"
] | Unified Multimodal Models (UMMs) have demonstrated remarkable performance in text-to-image generation (T2I) and editing (TI2I), whether instantiated as assembled unified frameworks which couple powerful vision-language model (VLM) with diffusion-based generator, or as naive Unified Multimodal Models with an early fusio... | generative models | https://openreview.net/pdf?id=IRrQgf2GAl | 2025-09-05T18:11:36 | 4 | [
{
"id": "qSTHsjq2LK",
"forum": "IRrQgf2GAl",
"review_number": 4,
"reviewer_id": "ICLR.cc/2026/Conference/Submission2376/Reviewer_Nkxi",
"reviewer_name": "Reviewer_Nkxi",
"rating": 4,
"confidence": 4,
"soundness": 3,
"contribution": 2,
"presentation": 3,
"summary": "1. Wel... | |
KKA59ai0x6 | https://openreview.net/forum?id=KKA59ai0x6 | Beyond Classification Accuracy: Neural-MedBench and the Need for Deeper Reasoning Benchmarks | 6 | 4 | [
4,
6,
8
] | [
3,
4,
5
] | 3 | [
"vision-language models",
"benchmark dataset",
"medical AI evaluation",
"reasoning-intensive tasks"
] | Recent advances in vision-language models (VLMs) have achieved remarkable performance on standard medical benchmarks, yet their true clinical reasoning ability remains unclear. Existing datasets predominantly emphasize classification accuracy, creating an evaluation illusion in which models appear proficient while stil... | We introduce Neural-MedBench, a reasoning-intensive benchmark that exposes how state-of-the-art vision-language models fail at clinical diagnosis despite excelling on standard medical AI benchmarks. | datasets and benchmarks | https://openreview.net/pdf?id=KKA59ai0x6 | 2025-09-19T18:43:36 | 4 | [
{
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"reviewer_id": "ICLR.cc/2026/Conference/Submission17633/Reviewer_Kijm",
"reviewer_name": "Reviewer_Kijm",
"rating": 4,
"confidence": 3,
"soundness": 3,
"contribution": 2,
"presentation": 3,
"summary": "This ... |
jqbYkKrP7k | https://openreview.net/forum?id=jqbYkKrP7k | APEX: One-Step High-Resolution Image Synthesis | 5.5 | 3.5 | [
4,
6,
4,
8
] | [
4,
4,
3,
3
] | 4 | [
"Diffusion",
"T2I"
] | The pursuit of efficient text-to-image synthesis has driven the field toward a few-step generation paradigm, yet this endeavor is hampered by a persistent trilemma: achieving high fidelity, inference efficiency, and training efficiency simultaneously remains elusive.
Current approaches are often forced into a difficult... | generative models | https://openreview.net/pdf?id=jqbYkKrP7k | 2025-09-01T23:53:20 | 4 | [
{
"id": "fSnhowl2Az",
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"reviewer_name": "Reviewer_pjrF",
"rating": 4,
"confidence": 4,
"soundness": 2,
"contribution": 2,
"presentation": 2,
"summary": "This pa... | |
DQuWpKLNwd | https://openreview.net/forum?id=DQuWpKLNwd | Reasoning on a Spectrum: Aligning LLMs to System 1 and System 2 Thinking | 4.8 | 3.6 | [
6,
4,
2,
6,
6
] | [
2,
4,
4,
3,
5
] | 5 | [
"Alignment",
"System 1 and System 2 thinking",
"Cognitive heuristics",
"LLM",
"NLP"
] | Large Language Models (LLMs) exhibit impressive reasoning abilities, yet their reliance on structured step-by-step processing reveals a critical limitation. In contrast, human cognition fluidly adapts between intuitive, heuristic (System 1) and analytical, deliberative (System 2) reasoning depending on the context. Thi... | foundation or frontier models, including LLMs | https://openreview.net/pdf?id=DQuWpKLNwd | 2025-09-20T06:07:23 | 5 | [
{
"id": "mPPshzgH6b",
"forum": "DQuWpKLNwd",
"review_number": 5,
"reviewer_id": "ICLR.cc/2026/Conference/Submission21612/Reviewer_6SYb",
"reviewer_name": "Reviewer_6SYb",
"rating": 6,
"confidence": 2,
"soundness": 3,
"contribution": 3,
"presentation": 4,
"summary": "This ... | |
rBFDvZu6pb | https://openreview.net/forum?id=rBFDvZu6pb | Towards Spatial Supersensing in Video | 5.5 | 3.75 | [
6,
6,
4,
6
] | [
4,
4,
4,
3
] | 4 | [
"Multimodal Large Langauge Model",
"Super Sensing Model",
"Spatial Understanding",
"Video Understanding",
"Memory"
] | We frame spatial supersensing in video as an overarching goal for multimodal intelligence and argue that progress requires a shift from long-context brute force to predictive sensing. Using a four-level taxonomy: semantic perception, streaming event cognition, implicit 3D spatial cognition, and predictive world modelin... | applications to computer vision, audio, language, and other modalities | https://openreview.net/pdf?id=rBFDvZu6pb | 2025-09-02T22:01:39 | 4 | [
{
"id": "ARkBhiaNDQ",
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"reviewer_id": "ICLR.cc/2026/Conference/Submission875/Reviewer_jh5E",
"reviewer_name": "Reviewer_jh5E",
"rating": 6,
"confidence": 4,
"soundness": 2,
"contribution": 3,
"presentation": 3,
"summary": "This wo... | |
3IaP48VUes | https://openreview.net/forum?id=3IaP48VUes | Can Aha Moments Be Fake? Identifying True and Decorative Thinking Steps in Chain-of-Thought | 4.5 | 3.5 | [
4,
4,
4,
6
] | [
3,
4,
3,
4
] | 4 | [
"Faithfulness; Reasoning; LLMs; steering"
] | Recent large language models (LLMs) can generate long Chain-of-Thought (CoT)
at test time, enabling them to solve complex tasks. These reasoning traces are often
assumed as a faithful reflection of LLMs’ internal thinking process, and can be
used for monitoring LLMs’ unsafe intentions. However, by analyzing the step-wi... | interpretability and explainable AI | https://openreview.net/pdf?id=3IaP48VUes | 2025-09-14T01:53:30 | 4 | [
{
"id": "YDcvohyjug",
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"reviewer_id": "ICLR.cc/2026/Conference/Submission4893/Reviewer_y5rC",
"reviewer_name": "Reviewer_y5rC",
"rating": 4,
"confidence": 3,
"soundness": 2,
"contribution": 2,
"presentation": 2,
"summary": "This p... | |
DDuF4lpcTl | https://openreview.net/forum?id=DDuF4lpcTl | HarmoMoE: Unifying Domain-Specialized Experts into a Mixture-of-Experts Model under Privacy Constraints | 5 | 3.25 | [
4,
4,
6,
6
] | [
4,
3,
3,
3
] | 4 | [
"Mixture of Experts",
"Privacy-Preserving Learning"
] | Mixture-of-Experts (MoE) models offer a powerful way to scale capacity, but existing designs typically assume centralized access to all training data. In many real-world scenarios, however, data is distributed across clients from different domains and cannot be shared due to privacy constraints, making it challenging t... | other topics in machine learning (i.e., none of the above) | https://openreview.net/pdf?id=DDuF4lpcTl | 2025-09-18T11:13:35 | 4 | [
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"reviewer_name": "Reviewer_pz7X",
"rating": 4,
"confidence": 4,
"soundness": 3,
"contribution": 2,
"presentation": 4,
"summary": "The a... | |
RzFdZ5Pjy6 | https://openreview.net/forum?id=RzFdZ5Pjy6 | Deception in Dialogue: Evaluating and Mitigating Deceptive Behavior in Large Language Models | 4 | 3.333333 | [
2,
4,
6
] | [
4,
4,
2
] | 3 | [
"Large Language Models (LLMs)",
"Reinforcement Learning",
"AI Safety"
] | Large Language Models (LLMs) now interact with hundreds of millions of people worldwide, powering applications such as customer support, education and healthcare. However, their ability to produce deceptive outputs, whether intentionally or inadvertently, poses significant safety concerns. The unpredictable nature of L... | Across 8 LLM models, we find deceptive behavior in dialogue in up to 43% dial and reduce it by 15% via reinforcement learning with a new deception detection metric. | alignment, fairness, safety, privacy, and societal considerations | https://openreview.net/pdf?id=RzFdZ5Pjy6 | 2025-09-20T08:10:25 | 3 | [
{
"id": "lwPb4zcXxK",
"forum": "RzFdZ5Pjy6",
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"reviewer_id": "ICLR.cc/2026/Conference/Submission22167/Reviewer_e2am",
"reviewer_name": "Reviewer_e2am",
"rating": 2,
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"soundness": 2,
"contribution": 2,
"presentation": 2,
"summary": "The p... |
eAge74DIgk | https://openreview.net/forum?id=eAge74DIgk | LitExplorer: Training-Free Diffusion Guidance with Adaptive Exploration-Filtering Framework | 4 | 3.333333 | [
4,
4,
4
] | [
3,
3,
4
] | 3 | [
"Diffusion Model;Traning-free"
] | Diffusion models possess strong general generative capabilities, yet they remain insufficient when aligned with specific target objectives. Fine-tuning methods can enhance alignment but incur high training costs and face the risk of reward hacking. Consequently, training-free guidance mechanisms have emerged, which lev... | applications to computer vision, audio, language, and other modalities | https://openreview.net/pdf?id=eAge74DIgk | 2025-09-01T20:12:48 | 3 | [
{
"id": "CnRO9YAIb5",
"forum": "eAge74DIgk",
"review_number": 3,
"reviewer_id": "ICLR.cc/2026/Conference/Submission101/Reviewer_6kFr",
"reviewer_name": "Reviewer_6kFr",
"rating": 4,
"confidence": 3,
"soundness": 3,
"contribution": 2,
"presentation": 2,
"summary": "The pap... | |
sL0gkGGhLL | https://openreview.net/forum?id=sL0gkGGhLL | Inferring Attribute Subspaces from Visual Contexts | 3.5 | 3.5 | [
2,
4,
4,
4
] | [
4,
2,
4,
4
] | 4 | [
"visual attributes",
"diffusion",
"attribute subspace"
] | Recent advances in generative vision-language models have demonstrated remarkable capabilities in image synthesis, captioning, and multi-modal reasoning. Among their most intriguing behaviors is in-context learning, the ability to adapt to new tasks from just a few examples. While well-studied in language models, this ... | We propose Attribute Subspace Inference Tasks and develop a training setup that enables generative models to infer shared semantic attributes from just a few example images without labels, and to generate attribute-consistent images. | generative models | https://openreview.net/pdf?id=sL0gkGGhLL | 2025-09-19T16:40:18 | 4 | [
{
"id": "9sZRDVeFQF",
"forum": "sL0gkGGhLL",
"review_number": 4,
"reviewer_id": "ICLR.cc/2026/Conference/Submission17019/Reviewer_BDP5",
"reviewer_name": "Reviewer_BDP5",
"rating": 2,
"confidence": 4,
"soundness": 2,
"contribution": 2,
"presentation": 2,
"summary": "This ... |
GWjvweJDnG | https://openreview.net/forum?id=GWjvweJDnG | Offline Federated Deep Reinforcement Learning with Awareness of Expected Returns and Policy Inconsistency | 4 | 3.25 | [
4,
4,
6,
2
] | [
4,
2,
3,
4
] | 4 | [
"Federated Deep Reinforcement Learning; Offline Deep Reinforcement Learning"
] | Offline Federated Deep Reinforcement Learning (FDRL) methods aggregate multiple client-side offline Deep Reinforcement Learning (DRL) models, each trained locally, to facilitate knowledge sharing while preserving privacy. Existing offline FDRL methods assign client weights during global aggregation using either simple ... | This paper proposes an offline federated deep reinforcement learning framework that evaluates the capabilities of client models and the global model by combining policy inconsistency and expected return. | reinforcement learning | https://openreview.net/pdf?id=GWjvweJDnG | 2025-09-16T11:01:07 | 4 | [
{
"id": "8v3TBDfEE6",
"forum": "GWjvweJDnG",
"review_number": 4,
"reviewer_id": "ICLR.cc/2026/Conference/Submission6666/Reviewer_Sgzo",
"reviewer_name": "Reviewer_Sgzo",
"rating": 4,
"confidence": 4,
"soundness": 2,
"contribution": 2,
"presentation": 2,
"summary": "The pa... |
refcXHU1Nh | https://openreview.net/forum?id=refcXHU1Nh | SafeFlowMatcher: Safe and Fast Planning using Flow Matching with Control Barrier Functions | 6 | 3.4 | [
6,
4,
8,
4,
8
] | [
2,
3,
3,
5,
4
] | 5 | [
"Flow matching",
"Safety guarantees",
"Planning and Control"
] | Generative planners based on Flow Matching (FM) produce high-quality paths in a single or a few ODE steps, but their sampling dynamics offer no formal safety guarantees and can yield incomplete paths near constraints. We present \emph{SafeFlowMatcher}, a planning framework that couples FM with control barrier functions... | We propose SafeFlowMatcher, a novel method for safe and fast planning that couples flow matching with control barrier functions via a two-phase prediction–correction integrator | applications to robotics, autonomy, planning | https://openreview.net/pdf?id=refcXHU1Nh | 2025-09-20T15:05:16 | 5 | [
{
"id": "wxZe5w39jq",
"forum": "refcXHU1Nh",
"review_number": 5,
"reviewer_id": "ICLR.cc/2026/Conference/Submission24026/Reviewer_Jozp",
"reviewer_name": "Reviewer_Jozp",
"rating": 6,
"confidence": 2,
"soundness": 3,
"contribution": 3,
"presentation": 3,
"summary": "This ... |
lIIJDDxBrg | https://openreview.net/forum?id=lIIJDDxBrg | Empowering Protein Language Model for Sequence-Structure Co-Generation with Continuous Structure Tokens | 3.5 | 4 | [
4,
4,
4,
2
] | [
4,
4,
3,
5
] | 4 | [
"ai for science",
"protein language model",
"protein sequence-structure co-generation"
] | Proteins inherently possess a consistent sequence-structure duality. The abundance of protein sequence data, which can be readily represented as discrete tokens, has enabled fruitful developments in protein language models (pLMs). A key remaining challenge, however, is how to effectively integrate continuous structural... | applications to physical sciences (physics, chemistry, biology, etc.) | https://openreview.net/pdf?id=lIIJDDxBrg | 2025-09-09T21:26:35 | 4 | [
{
"id": "A9JjnJUGT4",
"forum": "lIIJDDxBrg",
"review_number": 4,
"reviewer_id": "ICLR.cc/2026/Conference/Submission3427/Reviewer_NCdP",
"reviewer_name": "Reviewer_NCdP",
"rating": 4,
"confidence": 4,
"soundness": 2,
"contribution": 2,
"presentation": 2,
"summary": "This p... | |
nhcz0uni55 | https://openreview.net/forum?id=nhcz0uni55 | QuArch: A Benchmark for Evaluating LLM Reasoning in Computer Architecture | 4 | 3.333333 | [
4,
6,
2
] | [
3,
2,
5
] | 3 | [
"benchmark",
"computer architecture",
"dataset",
"language models",
"question-answering"
] | The field of computer architecture, which bridges high-level software abstractions and low-level hardware implementations, remains absent from current large language model (LLM) evaluations. To this end, we present QuArch (pronounced 'quark'), the first benchmark designed to facilitate the development and evaluation of... | We present QuArch, the first question-answering benchmark for the field of computer architecture, and find state-of-the-art models struggle with skills that require higher-order thinking. | datasets and benchmarks | https://openreview.net/pdf?id=nhcz0uni55 | 2025-09-19T04:43:23 | 3 | [
{
"id": "kJmTQKHnJG",
"forum": "nhcz0uni55",
"review_number": 3,
"reviewer_id": "ICLR.cc/2026/Conference/Submission14083/Reviewer_YovW",
"reviewer_name": "Reviewer_YovW",
"rating": 4,
"confidence": 3,
"soundness": 3,
"contribution": 2,
"presentation": 3,
"summary": "This ... |
MG5UFZ2Fa2 | https://openreview.net/forum?id=MG5UFZ2Fa2 | Identifying Outcome-Oriented Root Causes via Cross Regression | 4 | 3.5 | [
6,
4,
4,
2
] | [
3,
4,
3,
4
] | 4 | [
"Root Causes",
"Regression Theory"
] | Root Cause Analysis (RCA) in complex and interconnected systems exhibits significant importance in fields such as microservice maintenance, and supply-chain management. By identifying every intervened variable, existing RCA methods have achieved remarkable progress in localizing and fixing anomalies. However, people ma... | This paper presents a regression-based approach for identifying all outcome-oriented,necessary root-causes. | causal reasoning | https://openreview.net/pdf?id=MG5UFZ2Fa2 | 2025-09-17T09:14:39 | 4 | [
{
"id": "zS0wvvhsfE",
"forum": "MG5UFZ2Fa2",
"review_number": 4,
"reviewer_id": "ICLR.cc/2026/Conference/Submission8165/Reviewer_9ih8",
"reviewer_name": "Reviewer_9ih8",
"rating": 6,
"confidence": 3,
"soundness": 3,
"contribution": 3,
"presentation": 3,
"summary": "The pa... |
ceYA0t4yZ1 | https://openreview.net/forum?id=ceYA0t4yZ1 | Bringing Light to the Threshold: Identification of Multi-Score Regression Discontinuity Effects with Application to LED Manufacturing | 5.333333 | 3 | [
8,
4,
4
] | [
3,
4,
2
] | 3 | [
"Causal Machine Learning",
"Regression Discontinuity Design",
"Treatment Effect Identification",
"Causal Inference Application"
] | The regression discontinuity design (RDD) is a widely used framework for threshold-based causal effect estimation in causal inference. Recent extensions incorporating machine learning (ML) adjustments have made RDD an appealing approach for researchers utilizing causal ML toolkits. However, many real-world applications... | We derive new identification results for the Multi-Score RDD framework and apply ML-adjusted RDD estimators to manufacturing data accordingly. | causal reasoning | https://openreview.net/pdf?id=ceYA0t4yZ1 | 2025-09-19T17:58:22 | 3 | [
{
"id": "qd52FzfsSF",
"forum": "ceYA0t4yZ1",
"review_number": 3,
"reviewer_id": "ICLR.cc/2026/Conference/Submission17425/Reviewer_rcgL",
"reviewer_name": "Reviewer_rcgL",
"rating": 8,
"confidence": 3,
"soundness": 4,
"contribution": 4,
"presentation": 4,
"summary": "Reaso... |
K3vdeJ4R0k | https://openreview.net/forum?id=K3vdeJ4R0k | Towards Scalable Distance-Enhanced Graph Neural Network | 3.5 | 4 | [
4,
2,
4,
4
] | [
5,
4,
4,
3
] | 4 | [
"Graph Neural Networks",
"Expressive Power",
"Distance Encoding",
"Scalability"
] | Graph neural networks (GNNs) have demonstrated significant advantages in graph mining tasks, but often suffer from limited expressive power. Among existing expressive GNNs, distance-enhanced GNNs (DE-GNNs) arise as promising ones due to their conceptual simplicity and alignment with the expressive needs of real-world a... | We propose a scalable distance-enhanced graph neural network which is expressive and can scale to large graphs. | learning on graphs and other geometries & topologies | https://openreview.net/pdf?id=K3vdeJ4R0k | 2025-09-18T22:10:18 | 4 | [
{
"id": "rVZo9bXFSp",
"forum": "K3vdeJ4R0k",
"review_number": 4,
"reviewer_id": "ICLR.cc/2026/Conference/Submission11912/Reviewer_LbV8",
"reviewer_name": "Reviewer_LbV8",
"rating": 4,
"confidence": 5,
"soundness": 3,
"contribution": 2,
"presentation": 3,
"summary": "This ... |
RVmjA3u4PQ | https://openreview.net/forum?id=RVmjA3u4PQ | A Dynamic Multiscale Anti-Aliasing Network for Time Series Forecasting | 4.5 | 4 | [
6,
4,
6,
2
] | [
4,
4,
3,
5
] | 4 | [
"time series forecasting",
"frequency",
"aliasing"
] | Real-world time series inherently exhibit complex temporal patterns. Within chaotic systems, significant mixing and entanglement occur between different time-varying modes. Given that time series exhibit distinctly different patterns at various sampling scales, downsampling to extract multiscale features is a common ap... | We propose a novel model named DMANet, a dynamic multiscale anti-aliasing network for time series forecasting tasks. | learning on time series and dynamical systems | https://openreview.net/pdf?id=RVmjA3u4PQ | 2025-09-18T23:58:44 | 4 | [
{
"id": "8Xq3Yo4Sjx",
"forum": "RVmjA3u4PQ",
"review_number": 4,
"reviewer_id": "ICLR.cc/2026/Conference/Submission12877/Reviewer_pqCd",
"reviewer_name": "Reviewer_pqCd",
"rating": 6,
"confidence": 4,
"soundness": 3,
"contribution": 2,
"presentation": 3,
"summary": "This ... |
FShQHrDyEO | https://openreview.net/forum?id=FShQHrDyEO | Route-and-Reason: Scaling Large Language Model Reasoning with Reinforced Model Router | 4 | 3.5 | [
4,
4,
6,
2
] | [
4,
3,
3,
4
] | 4 | [
"Model Router",
"Large Language Model",
"LLM Reasoning",
"Efficient Reasoning",
"Reinforcement Learning"
] | Chain-of-thought has been proven essential for enhancing the complex reasoning abilities of Large Language Models (LLMs), but it also leads to high computational costs. Recent advances have explored the method to route queries among multiple models and proved it as a promising approach. However, previous works directly... | applications to computer vision, audio, language, and other modalities | https://openreview.net/pdf?id=FShQHrDyEO | 2025-09-20T16:46:56 | 4 | [
{
"id": "FAST7jcXoK",
"forum": "FShQHrDyEO",
"review_number": 4,
"reviewer_id": "ICLR.cc/2026/Conference/Submission24566/Reviewer_gJ4a",
"reviewer_name": "Reviewer_gJ4a",
"rating": 4,
"confidence": 4,
"soundness": 2,
"contribution": 2,
"presentation": 2,
"summary": "This ... | |
vRwuBOxbsJ | https://openreview.net/forum?id=vRwuBOxbsJ | Solving Football by Exploiting Equilibrium Structure of 2p0s Differential Games with One-Sided Information | 5.2 | 2.8 | [
6,
6,
6,
6,
2
] | [
3,
3,
2,
2,
4
] | 5 | [
"Differential Game",
"Incomplete-Information Game",
"Game Theory"
] | For a two-player imperfect-information extensive-form game (IIEFG) with $K$ time steps and a player action space of size $U$, the game tree complexity is $U^{2K}$, causing existing IIEFG solvers to struggle with large or infinite $(U,K)$, e.g., differential games with continuous action spaces. To partially address this... | The paper highlights the limitations of current state-of-the-art when applied to solving one-sided incomplete information differential games with continuous actions, such as Football, and proposes scalable methods to solve the problem. | reinforcement learning | https://openreview.net/pdf?id=vRwuBOxbsJ | 2025-09-19T13:10:14 | 5 | [
{
"id": "rWFBuPMJfL",
"forum": "vRwuBOxbsJ",
"review_number": 5,
"reviewer_id": "ICLR.cc/2026/Conference/Submission16010/Reviewer_52aL",
"reviewer_name": "Reviewer_52aL",
"rating": 6,
"confidence": 3,
"soundness": 3,
"contribution": 3,
"presentation": 3,
"summary": "This ... |
3kvV1nfWVq | https://openreview.net/forum?id=3kvV1nfWVq | A$^2$FM: An Adaptive Agent Foundation Model for Tool-Aware Hybrid Reasoning | 5 | 3.5 | [
6,
4,
4,
6
] | [
4,
2,
3,
5
] | 4 | [
"Adaptive LLMs",
"Deep Research",
"Agent Reasoning"
] | Large language models split into two families: reasoning-centric LLMs, which strengthen internal chain-of-thought reasoning but cannot invoke external tools, and agentic LLMs, which learn to interact with environments and leverage tools but often lag in deep reasoning. This divide arises from fundamentally different tr... | We propose A²FM, a unified 32B model combining agentic, reasoning, and instant modes via adaptive routing and APO, achieving state-of-the-art accuracy with substantially improved cost efficiency. | foundation or frontier models, including LLMs | https://openreview.net/pdf?id=3kvV1nfWVq | 2025-09-15T11:16:48 | 4 | [
{
"id": "MqIUkmGYDd",
"forum": "3kvV1nfWVq",
"review_number": 4,
"reviewer_id": "ICLR.cc/2026/Conference/Submission5384/Reviewer_S9XP",
"reviewer_name": "Reviewer_S9XP",
"rating": 6,
"confidence": 4,
"soundness": 3,
"contribution": 3,
"presentation": 3,
"summary": "The pa... |
qBAV2DEvAC | https://openreview.net/forum?id=qBAV2DEvAC | Implicit bias produces neural scaling laws in learning curves, from perceptrons to deep networks | 5.5 | 3.25 | [
8,
8,
4,
2
] | [
3,
3,
3,
4
] | 4 | [
"Neural scaling laws",
"Implicit bias",
"Learning curves",
"Spectral complexity norm",
"Perceptron theory"
] | Scaling laws in deep learning -- empirical power-law relationships linking model performance to resource growth -- have emerged as simple yet striking regularities across architectures, datasets, and tasks. These laws are particularly impactful in guiding the design of state-of-the-art models, since they quantify the b... | We connect neural scaling laws in deep networks with the implicit bias induced by logistic losses through a surprisingly simple perceptron theory. | optimization | https://openreview.net/pdf?id=qBAV2DEvAC | 2025-09-19T22:22:30 | 4 | [
{
"id": "1y3Xchgyqs",
"forum": "qBAV2DEvAC",
"review_number": 4,
"reviewer_id": "ICLR.cc/2026/Conference/Submission18886/Reviewer_kC4U",
"reviewer_name": "Reviewer_kC4U",
"rating": 8,
"confidence": 3,
"soundness": 2,
"contribution": 3,
"presentation": 4,
"summary": "The a... |
dDHnO3Vhyj | https://openreview.net/forum?id=dDHnO3Vhyj | Closing the Gap Between Text and Speech Understanding in LLMs | 6 | 3.666667 | [
6,
6,
6
] | [
3,
4,
4
] | 3 | [
"Speech language models",
"large language models",
"multimodal language models",
"modality alignment",
"cross-modal alignment",
"cross-modal transfer",
"cross-modal distillation",
"modality gap",
"speech processing"
] | Large Language Models (LLMs) can be adapted to extend their text capabilities to speech inputs. However, these speech-adapted LLMs consistently underperform their text-based counterparts—and even cascaded pipelines—on language understanding tasks. We term this shortfall the text–speech understanding gap: the performanc... | applications to computer vision, audio, language, and other modalities | https://openreview.net/pdf?id=dDHnO3Vhyj | 2025-09-19T00:21:10 | 3 | [
{
"id": "VaU8OclD0v",
"forum": "dDHnO3Vhyj",
"review_number": 3,
"reviewer_id": "ICLR.cc/2026/Conference/Submission12987/Reviewer_nz78",
"reviewer_name": "Reviewer_nz78",
"rating": 6,
"confidence": 3,
"soundness": 3,
"contribution": 3,
"presentation": 3,
"summary": "This ... | |
dB6DYLpjw4 | https://openreview.net/forum?id=dB6DYLpjw4 | Neural Mutual Information Estimation in Real Time via Pre-trained Hypernetworks | 5.333333 | 3 | [
4,
6,
6
] | [
4,
3,
2
] | 3 | [
"statistical dependence",
"transformers",
"hypernetwork",
"mutual information"
] | Measuring statistical dependency between high-dimensional random variables is
fundamental to data science and machine learning. Neural mutual information
(MI) estimators offer a promising avenue, but they typically require costly test-
time iterative optimization for each new dataset, making them impractical for
real-t... | A pre-trained attention-based model for statistical dependence quantification, accurate, fast and differentiable | foundation or frontier models, including LLMs | https://openreview.net/pdf?id=dB6DYLpjw4 | 2025-09-05T15:45:02 | 3 | [
{
"id": "OWPGpQ7okY",
"forum": "dB6DYLpjw4",
"review_number": 3,
"reviewer_id": "ICLR.cc/2026/Conference/Submission2321/Reviewer_GWbp",
"reviewer_name": "Reviewer_GWbp",
"rating": 4,
"confidence": 4,
"soundness": 3,
"contribution": 2,
"presentation": 3,
"summary": "This p... |
x8tl75Yznn | https://openreview.net/forum?id=x8tl75Yznn | Optimizing Temporal and Spatial Efficiency for Chain-of-Thought Reasoning in Large Language Models | 4 | 3.25 | [
6,
4,
4,
2
] | [
3,
4,
3,
3
] | 4 | [
"Reasoning Model",
"Model Compression",
"Efficiency"
] | Chain-of-Thought (CoT) reasoning in Large Language Models (LLMs) achieves remarkable performance but suffers from significant computational overhead. CoT reasoning exhibits redundancy across two critical dimensions: temporal redundancy, where reasoning steps may be unnecessary, and spatial redundancy, where computatio... | We introduce TSAR, a training-free framework that dramatically accelerates LLM reasoning by adaptively reducing both unnecessary thinking steps and computational precision, achieving massive speedups without sacrificing accuracy. | foundation or frontier models, including LLMs | https://openreview.net/pdf?id=x8tl75Yznn | 2025-09-16T10:12:32 | 4 | [
{
"id": "vCihpHKjWK",
"forum": "x8tl75Yznn",
"review_number": 4,
"reviewer_id": "ICLR.cc/2026/Conference/Submission6555/Reviewer_tC8f",
"reviewer_name": "Reviewer_tC8f",
"rating": 6,
"confidence": 3,
"soundness": 2,
"contribution": 3,
"presentation": 2,
"summary": "The pa... |
OgiLGrPgw5 | https://openreview.net/forum?id=OgiLGrPgw5 | Structured Visual Landscape: Generating Preferred Representations in Multi-modal Biological and Artificial Neural Networks | 2.5 | 4.25 | [
2,
2,
2,
4
] | [
4,
4,
5,
4
] | 4 | [
"visual representation",
"preferred images",
"fMRI",
"EEG",
"generative models"
] | Understanding how neurons responding to visual stimulus inputs is an important question in both deep learning and neuroscience. It has significant implications in enhancing the interpretability of black-box artificial neural networks and understanding the visual representation in biological neural networks. We proposed... | Develop a structured visual representation landscape constrained by activations to generating preferred representations in biological and artificial neural networks | applications to neuroscience & cognitive science | https://openreview.net/pdf?id=OgiLGrPgw5 | 2025-09-19T11:38:14 | 4 | [
{
"id": "mDktuKfSgl",
"forum": "OgiLGrPgw5",
"review_number": 4,
"reviewer_id": "ICLR.cc/2026/Conference/Submission15607/Reviewer_QtiM",
"reviewer_name": "Reviewer_QtiM",
"rating": 2,
"confidence": 4,
"soundness": 2,
"contribution": 3,
"presentation": 2,
"summary": "This ... |
PifVwyqe5L | https://openreview.net/forum?id=PifVwyqe5L | RAG over Tables: Hierarchical Memory Index, Multi-Stage Retrieval, and Benchmarking | 3 | 4 | [
2,
2,
4,
4
] | [
4,
4,
4,
4
] | 4 | [
"Multi-table Question Answering",
"RAG"
] | Retrieval-Augmented Generation (RAG) enhances Large Language Models (LLMs) by integrating them with an external knowledge base to improve the answer relevance and accuracy. In real-world scenarios, beyond pure text, a substantial amount of knowledge is stored in tables, and user questions often require retrieving answe... | foundation or frontier models, including LLMs | https://openreview.net/pdf?id=PifVwyqe5L | 2025-09-17T11:02:10 | 4 | [
{
"id": "dIfFRlbPBY",
"forum": "PifVwyqe5L",
"review_number": 4,
"reviewer_id": "ICLR.cc/2026/Conference/Submission8309/Reviewer_cGTr",
"reviewer_name": "Reviewer_cGTr",
"rating": 2,
"confidence": 4,
"soundness": 2,
"contribution": 1,
"presentation": 2,
"summary": "This p... | |
bNanN941dw | https://openreview.net/forum?id=bNanN941dw | Offline Clustering of Linear Bandits: The Power of Clusters under Limited Data | 4 | 3.5 | [
4,
4,
2,
6
] | [
4,
3,
4,
3
] | 4 | [
"Offline Clustering of Bandits",
"Offline Bandits Algorithms",
"Data Insufficiency"
] | Contextual multi-armed bandit is a fundamental learning framework for making a sequence of decisions, e.g., advertising recommendations for a sequence of arriving users. Recent works have shown that clustering these users based on the similarity of their learned preferences can accelerate the learning. However, prior w... | This paper addresses the offline clustering of bandits problem, proposing algorithms and theoretical bounds to handle various amount of data scenarios effectively. | learning theory | https://openreview.net/pdf?id=bNanN941dw | 2025-09-19T10:35:42 | 4 | [
{
"id": "SPfGnb8W7F",
"forum": "bNanN941dw",
"review_number": 4,
"reviewer_id": "ICLR.cc/2026/Conference/Submission15255/Reviewer_R7Pr",
"reviewer_name": "Reviewer_R7Pr",
"rating": 4,
"confidence": 4,
"soundness": 3,
"contribution": 2,
"presentation": 3,
"summary": "The p... |
VRBKiWBPKZ | https://openreview.net/forum?id=VRBKiWBPKZ | Learning to Think in Blocks: A Prior-Guided Reinforcement Learning Framework for RAG | 3.5 | 3.5 | [
4,
4,
4,
2
] | [
2,
5,
3,
4
] | 4 | [
"Retrieval-Augmented Generation",
"Reinforcement Learning",
"Prior-Guided Learning",
"Structured Action Space",
"Query Rewriting"
] | Retrieval-Augmented Generation (RAG) systems mitigate factual inaccuracies in large language models (LLMs) by integrating external knowledge, but their effectiveness often hinges on query rewriting techniques. Prompt-based rewriting methods are frequently suboptimal, while existing reinforcement learning (RL) approache... | foundation or frontier models, including LLMs | https://openreview.net/pdf?id=VRBKiWBPKZ | 2025-09-20T16:28:24 | 4 | [
{
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"contribution": 3,
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8zbWMaREah | https://openreview.net/forum?id=8zbWMaREah | Neighborhood Sampling Does Not Learn the Same Graph Neural Network | 3 | 3.25 | [
4,
4,
2,
2
] | [
3,
4,
3,
3
] | 4 | [
"graph neural network",
"neighborhood sampling",
"neural tangent kernel",
"Gaussian process posterior inference"
] | Neighborhood sampling is an important ingredient in the training of large-scale graph neural networks. It suppresses the exponential growth of the neighborhood size across network layers and maintains feasible memory consumption and time costs. While it becomes a standard implementation in practice, its systemic behavi... | We analyze the training dynamics of graph neural networks under neighborhood sampling by using graph neural tangent kernels. | probabilistic methods (Bayesian methods, variational inference, sampling, UQ, etc.) | https://openreview.net/pdf?id=8zbWMaREah | 2025-09-20T08:00:54 | 4 | [
{
"id": "OI6EsX3lxG",
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"contribution": 3,
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"summary": "The p... |
vNZ420zDte | https://openreview.net/forum?id=vNZ420zDte | DREAM: Decoupled Reinforcement Learning with Reward Measurement for Large Language Model Test-time Training | 4 | 3.75 | [
4,
4,
6,
2
] | [
4,
4,
4,
3
] | 4 | [
"Reinforcement Learning",
"Test-Time Training",
"Large Language Model"
] | This paper studies the problem of large language model (LLM) test-time training, which aims to enhance the reasoning ability of LLMs via unlabeled test data. Recent works usually utilize majority voting to infer the labels of samples to guide the reinforcement learning process, which could be inaccurate and biased with... | reinforcement learning | https://openreview.net/pdf?id=vNZ420zDte | 2025-09-20T15:39:57 | 4 | [
{
"id": "W6CphpY9do",
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"reviewer_name": "Reviewer_eSoi",
"rating": 4,
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"contribution": 3,
"presentation": 3,
"summary": "The a... | |
VRKKkfE4im | https://openreview.net/forum?id=VRKKkfE4im | HyenaMoE: A Hybrid and Scalable Architecture for Efficient Genomic Modeling | 4 | 4 | [
4,
4,
4,
4
] | [
4,
5,
3,
4
] | 4 | [
"Genomics",
"Hyena",
"Foundation Models",
"Large Language Models",
"Mixture of Experts"
] | DNA sequences serve as the fundamental blueprint of cellular life, encoding critical information for gene regulation, protein synthesis, and a broad spectrum of essential biological processes. Owing to their sequential structure, DNA sequences bear similarities to natural language, motivating the adaptation of large la... | HyenaMoE: A Hybrid and Scalable Architecture for Efficient Genomic Modeling | foundation or frontier models, including LLMs | https://openreview.net/pdf?id=VRKKkfE4im | 2025-09-16T00:18:01 | 4 | [
{
"id": "l4EB7SyIPX",
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"reviewer_id": "ICLR.cc/2026/Conference/Submission6114/Reviewer_6WF8",
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"rating": 4,
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"soundness": 3,
"contribution": 2,
"presentation": 3,
"summary": "The pa... |
D0u0glT060 | https://openreview.net/forum?id=D0u0glT060 | Deconstructing Positional Information: From Attention Logits to Training Biases | 7.2 | 3.2 | [
8,
8,
4,
8,
8
] | [
3,
3,
4,
3,
3
] | 5 | [
"Position Encoding; Toeplitz Matrix; Attention Logit."
] | Positional encodings, a mechanism for incorporating sequential information into the Transformer model, are central to contemporary research on neural architectures. Previous work has largely focused on understanding their function through the principle of distance attenuation, where proximity dictates influence. Howeve... | We propose a unifying perspective on the role of positional encoding and discover that rope training exhibits implicit biases. | interpretability and explainable AI | https://openreview.net/pdf?id=D0u0glT060 | 2025-09-08T23:14:37 | 5 | [
{
"id": "KE0SbyfDt5",
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"reviewer_id": "ICLR.cc/2026/Conference/Submission3159/Reviewer_hmEf",
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"rating": 8,
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"contribution": 3,
"presentation": 4,
"summary": "The pa... |
VQJFDRLeTK | https://openreview.net/forum?id=VQJFDRLeTK | Efficient Edge Test-Time Adaptation via Latent Feature Coordinate Correction | 3.5 | 4.5 | [
4,
2,
2,
6
] | [
4,
4,
5,
5
] | 4 | [
"Test-time Adaptation",
"Edge Devices",
"Forward-Only",
"Latent Feature"
] | Edge devices face significant challenges due to limited computational resources and distribution shifts, making efficient and adaptable machine learning essential. Existing test-time adaptation (TTA) methods often rely on gradient-based optimization or batch processing, which are inherently unsuitable for resource-cons... | An efficient single-instance TTA method for edge devices, leveraging forward-only optimization in the latent principal subspace. | transfer learning, meta learning, and lifelong learning | https://openreview.net/pdf?id=VQJFDRLeTK | 2025-09-01T22:58:57 | 4 | [
{
"id": "0voDlOpRwx",
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"rating": 4,
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"soundness": 2,
"contribution": 2,
"presentation": 2,
"summary": "This pa... |
wNAUAPfceN | https://openreview.net/forum?id=wNAUAPfceN | Guided Star-Shaped Masked Diffusion | 5.5 | 3 | [
4,
6,
6,
6
] | [
3,
3,
3,
3
] | 4 | [
"Discrete Diffusion",
"Text Diffusion Models",
"Masked Diffusion",
"Guided Sampling"
] | The performance of pre-trained masked diffusion models is often constrained by their sampling procedure, which makes decisions irreversible and struggles in low-step generation regimes. We introduce a novel sampling algorithm that works with pre-trained models and, after a lightweight fine-tuning of a single layer, sig... | We developed a new sampling algorithm that, with minimal fine-tuning, enables pre-trained diffusion models to self-correct, significantly boosting quality in few-step generation. | generative models | https://openreview.net/pdf?id=wNAUAPfceN | 2025-09-20T19:04:35 | 4 | [
{
"id": "NHDYmW21X8",
"forum": "wNAUAPfceN",
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"reviewer_id": "ICLR.cc/2026/Conference/Submission25294/Reviewer_sA7a",
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"rating": 4,
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"contribution": 3,
"presentation": 3,
"summary": "The p... |
bs890te4so | https://openreview.net/forum?id=bs890te4so | Out-of-distributon Tests Reveal Compositionality in Chess Transformers | 2.666667 | 4.666667 | [
2,
2,
4
] | [
5,
5,
4
] | 3 | [
"Language model",
"transformer",
"chess model",
"out-of-distribution generalization",
"rule extrapolation",
"chess960"
] | Chess is a canonical example of a task that requires rigorous reasoning and long-term planning. Modern decision Transformers - trained similarly to LLMs - are able to learn competent gameplay, but it is unclear to what extent they truly capture the rules of chess.
To investigate this, we train a 270M parameter chess Tr... | foundation or frontier models, including LLMs | https://openreview.net/pdf?id=bs890te4so | 2025-09-20T04:53:16 | 3 | [
{
"id": "J1R1Dk7eeO",
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"rating": 2,
"confidence": 5,
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"contribution": 1,
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"summary": "The p... | |
ggONlqUsUY | https://openreview.net/forum?id=ggONlqUsUY | Isolation-based Spherical Ensemble Representations for Anomaly Detection | 3.5 | 3.5 | [
4,
4,
2,
4
] | [
4,
3,
4,
3
] | 4 | [
"Anomaly Detection",
"Unsupervised Learning",
"Isolation Forest"
] | Anomaly detection is a critical task in data mining and management with applications spanning fraud detection, network security, and log monitoring. Despite extensive research, existing unsupervised anomaly detection methods still face fundamental challenges including conflicting distributional assumptions, computation... | unsupervised, self-supervised, semi-supervised, and supervised representation learning | https://openreview.net/pdf?id=ggONlqUsUY | 2025-09-15T17:09:33 | 4 | [
{
"id": "oQ9kqGERU2",
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"review_number": 4,
"reviewer_id": "ICLR.cc/2026/Conference/Submission5690/Reviewer_vDkB",
"reviewer_name": "Reviewer_vDkB",
"rating": 4,
"confidence": 4,
"soundness": 3,
"contribution": 2,
"presentation": 3,
"summary": "This p... | |
5og80LMVxG | https://openreview.net/forum?id=5og80LMVxG | Latent Wavelet Diffusion For Ultra High-Resolution Image Synthesis | 4.5 | 4 | [
4,
6,
4,
4
] | [
4,
4,
4,
4
] | 4 | [
"Generative Models",
"Diffusion Models",
"Wavelet",
"Ultra High-Resolution"
] | High-resolution image synthesis remains a core challenge in generative modeling, particularly in balancing computational efficiency with the preservation of fine-grained visual detail. We present $\textit{Latent Wavelet Diffusion (LWD)}$, a lightweight training framework that significantly improves detail and texture f... | We enhance Ultra High-Resolution image generation by decomposing latent features into wavelet subbands, allowing the model to focus on frequency-specific refinement during diffusion. | generative models | https://openreview.net/pdf?id=5og80LMVxG | 2025-09-19T23:47:57 | 4 | [
{
"id": "m3wUaWedUV",
"forum": "5og80LMVxG",
"review_number": 4,
"reviewer_id": "ICLR.cc/2026/Conference/Submission19510/Reviewer_9QM1",
"reviewer_name": "Reviewer_9QM1",
"rating": 4,
"confidence": 4,
"soundness": 3,
"contribution": 2,
"presentation": 3,
"summary": "This ... |
FFnbfI84bP | https://openreview.net/forum?id=FFnbfI84bP | FairMedQA: Benchmarking Bias in Large Language Models for Medicine and Healthcare | 3.333333 | 3.666667 | [
4,
2,
4
] | [
4,
4,
3
] | 3 | [
"LLM Bias",
"Medical QA",
"Adversarial Testing",
"Bias Benchmark"
] | Large language models (LLMs) are reaching expert-level accuracy on medical diagnosis questions, yet their underlying biases pose life-critical risks. Bias linked to race, sex, and socioeconomic status is well documented in clinical settings, but a consistent, automatic testbed and a large-scale empirical study across m... | We introduce FairMedQA and use it benchmark medical bias in LLMs cross models and versions | alignment, fairness, safety, privacy, and societal considerations | https://openreview.net/pdf?id=FFnbfI84bP | 2025-09-19T02:50:59 | 3 | [
{
"id": "hWGb7PRMUA",
"forum": "FFnbfI84bP",
"review_number": 3,
"reviewer_id": "ICLR.cc/2026/Conference/Submission13715/Reviewer_cWHL",
"reviewer_name": "Reviewer_cWHL",
"rating": 4,
"confidence": 4,
"soundness": 3,
"contribution": 2,
"presentation": 3,
"summary": "This ... |
v1p4bDnDAP | https://openreview.net/forum?id=v1p4bDnDAP | Two Birds with One Stone: Neural Tangent Kernel for Efficient and Robust Gradual Domain Adaptation | 4.666667 | 3.333333 | [
6,
6,
2
] | [
3,
3,
4
] | 3 | [
"Gradual Domain Adaptation",
"distribution shift",
"Neural Tangent Kernel",
"Out-of-distribution Generalization"
] | Gradual Domain Adaptation (GDA) bridges large distribution shifts through intermediate domains, yet faces challenges in computational overhead and error accumulation. In view of these problems, we propose GradNTK, a novel framework to employ the Neural Tangent Kernel (NTK) as one stone to "hit" two birds of the efficie... | One kernel, two roles: short-time NTK yields a differentiable NTK-MMD for smooth alignment and a utility score for per-sample weighting, enabling near-linear, single-pass GDA. | transfer learning, meta learning, and lifelong learning | https://openreview.net/pdf?id=v1p4bDnDAP | 2025-09-13T17:43:27 | 3 | [
{
"id": "GE1KUn4tGp",
"forum": "v1p4bDnDAP",
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"reviewer_id": "ICLR.cc/2026/Conference/Submission4746/Reviewer_ZvRF",
"reviewer_name": "Reviewer_ZvRF",
"rating": 6,
"confidence": 3,
"soundness": 3,
"contribution": 3,
"presentation": 3,
"summary": "This w... |
7ZD9fSljxY | https://openreview.net/forum?id=7ZD9fSljxY | Robust Forecasting of Network Systems Subject to Topology Perturbation | 4 | 2.75 | [
4,
4,
6,
2
] | [
2,
2,
3,
4
] | 4 | [
"Robust Learning",
"Network Forecasting",
"Bayesian Coresets",
"Model Reduction"
] | Many real-world dynamical systems, such as epidemic, traffic, and logistics networks, consist of sparsely interacting components and thus naturally exhibit an underlying graph structure. Forecasting their evolution is computationally challenging due to high dimensionality and is further complicated by measurement noise... | We propose a forecasting scheme for network time series that is robust to topology perturbation. | learning on time series and dynamical systems | https://openreview.net/pdf?id=7ZD9fSljxY | 2025-09-19T05:29:37 | 4 | [
{
"id": "sB42mkqi59",
"forum": "7ZD9fSljxY",
"review_number": 4,
"reviewer_id": "ICLR.cc/2026/Conference/Submission14239/Reviewer_BzyQ",
"reviewer_name": "Reviewer_BzyQ",
"rating": 4,
"confidence": 2,
"soundness": 2,
"contribution": 2,
"presentation": 2,
"summary": "The p... |
uAkexWJ7dW | https://openreview.net/forum?id=uAkexWJ7dW | Robust Selective Activation with Randomized Temporal K-Winner-Take-All in Spiking Neural Networks for Continual Learning | 6 | 4.25 | [
4,
6,
8,
6
] | [
3,
5,
5,
4
] | 4 | [
"Spiking neural networks"
] | The human brain exhibits remarkable efficiency in processing sequential information, a capability deeply rooted in the temporal selectivity and stochastic competition of neuronal activation. Current continual learning in spiking neural networks (SNNs) faces a critical challenge: balancing task-specific selectivity with... | applications to neuroscience & cognitive science | https://openreview.net/pdf?id=uAkexWJ7dW | 2025-09-18T21:53:46 | 4 | [
{
"id": "E5Azytfs2Y",
"forum": "uAkexWJ7dW",
"review_number": 4,
"reviewer_id": "ICLR.cc/2026/Conference/Submission11765/Reviewer_X1JP",
"reviewer_name": "Reviewer_X1JP",
"rating": 4,
"confidence": 3,
"soundness": 3,
"contribution": 3,
"presentation": 3,
"summary": "This ... | |
mSSoedJ2h5 | https://openreview.net/forum?id=mSSoedJ2h5 | Prover Agent: An Agent-Based Framework for Formal Mathematical Proofs | 4 | 4 | [
8,
4,
2,
2
] | [
3,
4,
5,
4
] | 4 | [
"Agent",
"Formal Theorem Proving",
"Automated Theorem Proving",
"Small Language Model"
] | We present Prover Agent, a novel AI agent for automated theorem proving that integrates large language models (LLMs) with a formal proof assistant, Lean. Prover Agent coordinates an informal reasoning LLM, a formal prover model, and feedback from Lean while also generating auxiliary lemmas to assist in discovering the ... | We present Prover Agent, an AI agent for automated theorem proving that integrates LLMs with Lean and auxiliary lemma generation, achieving 88.1% on MiniF2F, the new SOTA among methods using small language models. | neurosymbolic & hybrid AI systems (physics-informed, logic & formal reasoning, etc.) | https://openreview.net/pdf?id=mSSoedJ2h5 | 2025-09-19T21:22:57 | 4 | [
{
"id": "qGZAScgChL",
"forum": "mSSoedJ2h5",
"review_number": 4,
"reviewer_id": "ICLR.cc/2026/Conference/Submission18484/Reviewer_rWUY",
"reviewer_name": "Reviewer_rWUY",
"rating": 8,
"confidence": 3,
"soundness": 3,
"contribution": 3,
"presentation": 4,
"summary": "The g... |
h7g3HflcxE | https://openreview.net/forum?id=h7g3HflcxE | BAQ: Efficient Bit Allocation Quantization for Large Language Models | 2.5 | 4.5 | [
2,
2,
4,
2
] | [
4,
4,
5,
5
] | 4 | [
"model compression",
"post training quantization",
"weight-only quantization",
"bit allocation"
] | Post-training model quantization is a widely adopted technique for reducing the memory and computational costs of large language models (LLMs). However, most existing methods either fix a uniform bitwidth or rely on binary sensitivity groupings (``sensitive'' vs.\ ``non-sensitive'') that treat all weights within a grou... | foundation or frontier models, including LLMs | https://openreview.net/pdf?id=h7g3HflcxE | 2025-09-19T22:26:29 | 4 | [
{
"id": "2r3Huvp7fn",
"forum": "h7g3HflcxE",
"review_number": 4,
"reviewer_id": "ICLR.cc/2026/Conference/Submission18920/Reviewer_cJWm",
"reviewer_name": "Reviewer_cJWm",
"rating": 2,
"confidence": 4,
"soundness": 2,
"contribution": 2,
"presentation": 2,
"summary": "The p... | |
BlbLPArfCD | https://openreview.net/forum?id=BlbLPArfCD | MoST: Mixing Speech and Text with Modality-Aware Mixture of Experts | 4.666667 | 3 | [
6,
4,
4
] | [
3,
3,
3
] | 3 | [
"Mixture of Experts",
"Speech Language Model",
"Multimodal Language Model"
] | We present MoST (Mixture of Speech and Text), a novel multimodal large language model that seamlessly integrates speech and text processing through our proposed Modality-Aware Mixture of Experts (MAMoE) architecture. While current multimodal models typically process diverse modality representations with identical para... | foundation or frontier models, including LLMs | https://openreview.net/pdf?id=BlbLPArfCD | 2025-09-18T19:57:20 | 3 | [
{
"id": "mTjQ60WWdz",
"forum": "BlbLPArfCD",
"review_number": 3,
"reviewer_id": "ICLR.cc/2026/Conference/Submission11337/Reviewer_pG6E",
"reviewer_name": "Reviewer_pG6E",
"rating": 6,
"confidence": 3,
"soundness": 3,
"contribution": 3,
"presentation": 3,
"summary": "The p... | |
OSVlYfp9Po | https://openreview.net/forum?id=OSVlYfp9Po | REPRESENTATION LEARNING ON NATIVE CORTICAL SURFACES: FROM GEOMETRY TO INDIVIDUAL TRAITS | 3.333333 | 3.666667 | [
2,
4,
4
] | [
5,
4,
2
] | 3 | [
"cortical surface",
"self-attention",
"transformer"
] | Analyzing the intricate geometry of the cerebral cortex is fundamental to understanding the neuroanatomical basis of individual traits. However, the fundamental conflict between powerful, grid-dependent architectures like Transformers and the irregular cortical mesh has forced a compromise: the distortive practice of s... | applications to neuroscience & cognitive science | https://openreview.net/pdf?id=OSVlYfp9Po | 2025-09-19T16:09:24 | 3 | [
{
"id": "GiVddMgAR8",
"forum": "OSVlYfp9Po",
"review_number": 3,
"reviewer_id": "ICLR.cc/2026/Conference/Submission16848/Reviewer_7orw",
"reviewer_name": "Reviewer_7orw",
"rating": 2,
"confidence": 5,
"soundness": 1,
"contribution": 2,
"presentation": 2,
"summary": "This ... | |
BViZkEr0IA | https://openreview.net/forum?id=BViZkEr0IA | The Mechanistic Emergence of Symbol Grounding in Language Models | 4.8 | 3.4 | [
6,
4,
6,
6,
2
] | [
3,
4,
3,
4,
3
] | 5 | [
"Language Grounding",
"Mechanistic Interpretability",
"Language Models"
] | Symbol grounding (Harnad, 1990) describes how symbols such as words acquire their meanings by connecting to real-world sensorimotor experiences.
Recent work has shown preliminary evidence that grounding may emerge in (vision-)language models trained at scale without using explicit grounding objectives.
Yet, the specif... | We provide behavioral and mechanistic evidence that symbol grounding can emerge in autoregressive language models. | interpretability and explainable AI | https://openreview.net/pdf?id=BViZkEr0IA | 2025-09-03T23:25:43 | 5 | [
{
"id": "cOhLjeRZfB",
"forum": "BViZkEr0IA",
"review_number": 5,
"reviewer_id": "ICLR.cc/2026/Conference/Submission1734/Reviewer_P6pG",
"reviewer_name": "Reviewer_P6pG",
"rating": 6,
"confidence": 3,
"soundness": 3,
"contribution": 3,
"presentation": 4,
"summary": "This p... |
i6YOXKtzqN | https://openreview.net/forum?id=i6YOXKtzqN | Decoupled Diffusion Models for Efficient Spatio-Temporal Graph Forecasting | 4 | 4 | [
4,
4,
4
] | [
4,
5,
3
] | 3 | [
"spatio-temporal graph forecasting",
"probabilistic forecasting",
"diffusion model",
"decoupled graph neural network"
] | Graph-based diffusion models suffer from a critical computational bottleneck, limiting their use in practical applications such as spatio-temporal graph forecasting. We argue that this inefficiency stems from the fusion of information propagation and feature transformation within standard GNNs. In this paper, we introd... | learning on graphs and other geometries & topologies | https://openreview.net/pdf?id=i6YOXKtzqN | 2025-09-09T13:25:01 | 3 | [
{
"id": "avOTxGvzW8",
"forum": "i6YOXKtzqN",
"review_number": 3,
"reviewer_id": "ICLR.cc/2026/Conference/Submission3291/Reviewer_2Acj",
"reviewer_name": "Reviewer_2Acj",
"rating": 4,
"confidence": 4,
"soundness": 3,
"contribution": 2,
"presentation": 3,
"summary": "The pa... | |
ni3BIqhCzw | https://openreview.net/forum?id=ni3BIqhCzw | On the Generalization of Dynamic GNNs: A Heavy-Tailed Wavelet Perspective | 2.666667 | 2.666667 | [
4,
2,
2
] | [
2,
3,
3
] | 3 | [
"dynamic F"
] | Dynamic graphs exhibit bursty and intermittent dynamics that are poorly captured by standard sequence models. We take a signal–statistical view and show that node-wise temporal signals, once transformed into wavelet space, display Pareto-type heavy tails: a small set of high-magnitude coefficients concentrates a large ... | learning theory | https://openreview.net/pdf?id=ni3BIqhCzw | 2025-09-19T12:29:54 | 3 | [
{
"id": "s3ax65sgUZ",
"forum": "ni3BIqhCzw",
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"reviewer_id": "ICLR.cc/2026/Conference/Submission15857/Reviewer_3vf2",
"reviewer_name": "Reviewer_3vf2",
"rating": 4,
"confidence": 2,
"soundness": 2,
"contribution": 2,
"presentation": 2,
"summary": "The p... | |
4w9HzBBLRk | https://openreview.net/forum?id=4w9HzBBLRk | Towards Multimodal Understanding, Reasoning, and Tool Usage across Vision, Speech, and Audio in Long Videos | 4 | 4.5 | [
4,
4,
4,
4
] | [
4,
5,
5,
4
] | 4 | [
"multimodal",
"long-form video understanding",
"benchmark",
"agentic pipeline",
"question answering",
"scenario-driven QA"
] | Long-form, multimodal video understanding requires models to integrate vision, speech, and ambient audio while reasoning coherently over extended contexts. However, existing benchmarks often emphasize either long temporal contexts or rich multimodal content, but rarely both. Moreover, they are typically restricted to m... | STARBench is a human-validated benchmark for long-form multimodal video understanding, and STARAgent is an agentic pipeline for multimodal long video understanding, together exposing current state-of-the-art MLLMs’ limits | datasets and benchmarks | https://openreview.net/pdf?id=4w9HzBBLRk | 2025-09-20T19:04:54 | 4 | [
{
"id": "VLoZTY39Fl",
"forum": "4w9HzBBLRk",
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"reviewer_name": "Reviewer_bBJM",
"rating": 4,
"confidence": 4,
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"contribution": 2,
"presentation": 3,
"summary": "This ... |
ifesxQxlJp | https://openreview.net/forum?id=ifesxQxlJp | Amplitude-based Input Attribution in Quantum Learning via Integrated Gradients | 3 | 4.25 | [
0,
4,
4,
4
] | [
5,
4,
4,
4
] | 4 | [
"Quantum Computing",
"Quantum Machine Learning",
"Interpretability in QML"
] | Quantum machine learning (QML) algorithms have demonstrated early promise across hardware platforms, but remain difficult to interpret due to the inherent opacity of quantum state evolution. Widely-used classical interpretability methods, such as integrated gradients and surrogate-based sensitivity analysis, are not di... | We introduce HattriQ, a technique for computing the input attribution scores of quantum machine learning models. | other topics in machine learning (i.e., none of the above) | https://openreview.net/pdf?id=ifesxQxlJp | 2025-09-19T07:25:06 | 4 | [
{
"id": "oULR5R3uMm",
"forum": "ifesxQxlJp",
"review_number": 4,
"reviewer_id": "ICLR.cc/2026/Conference/Submission14522/Reviewer_iYGU",
"reviewer_name": "Reviewer_iYGU",
"rating": 0,
"confidence": 5,
"soundness": 3,
"contribution": 2,
"presentation": 3,
"summary": "The p... |
QTh3aRcbTt | https://openreview.net/forum?id=QTh3aRcbTt | Improved Regret for Decentralized Online Convex Optimization with Compressed Communication | 3 | 3.5 | [
2,
4,
2,
4
] | [
4,
2,
4,
4
] | 4 | [
"Decentralized Online Convex Optimization",
"Compressed Communication"
] | We investigate decentralized online convex optimization with compressed communication, where $n$ learners collaboratively minimize a sequence of global loss functions using only local information and compressed data from their neighbors. Prior work has established regret bounds of $O(\max\\{\omega^{-2}\rho^{-4}n^{1/2}... | optimization | https://openreview.net/pdf?id=QTh3aRcbTt | 2025-09-18T21:02:24 | 4 | [
{
"id": "qyCnlHDAla",
"forum": "QTh3aRcbTt",
"review_number": 4,
"reviewer_id": "ICLR.cc/2026/Conference/Submission11508/Reviewer_kFty",
"reviewer_name": "Reviewer_kFty",
"rating": 2,
"confidence": 4,
"soundness": 3,
"contribution": 3,
"presentation": 2,
"summary": "This ... | |
4zoMnmZzh4 | https://openreview.net/forum?id=4zoMnmZzh4 | VisCoder2: Building Multi-Language Visualization Coding Agents | 5.5 | 3.75 | [
8,
4,
8,
2
] | [
4,
4,
3,
4
] | 4 | [
"Code Models",
"Visualization",
"Fine-tuning"
] | Large language models (LLMs) have recently enabled coding agents capable of generating, executing, and revising visualization code. However, existing models often fail in practical workflows due to limited language coverage, unreliable execution, and lack of iterative correction mechanisms. Progress has been constraine... | generative models | https://openreview.net/pdf?id=4zoMnmZzh4 | 2025-09-19T18:53:05 | 4 | [
{
"id": "axI3jKVnz3",
"forum": "4zoMnmZzh4",
"review_number": 4,
"reviewer_id": "ICLR.cc/2026/Conference/Submission17682/Reviewer_R3P7",
"reviewer_name": "Reviewer_R3P7",
"rating": 8,
"confidence": 4,
"soundness": 3,
"contribution": 3,
"presentation": 1,
"summary": "This ... | |
xQRAo9YUQ3 | https://openreview.net/forum?id=xQRAo9YUQ3 | RAST-MoE-RL: A Regime-Aware Spatio-Temporal MoE Framework for Deep Reinforcement Learning in Ride-Hailing | 5 | 3.75 | [
4,
6,
6,
4
] | [
4,
3,
4,
4
] | 4 | [
"Deep Reinforcement Learning",
"Mixture of Experts",
"Urban Mobility",
"Ride-Hailing"
] | Ride-hailing platforms face the challenge of balancing passenger waiting times with overall system efficiency under highly uncertain supply–demand conditions. Adaptive delayed matching, which decides whether to assign drivers immediately or hold requests for batching, creates a fundamental trade-off between matching de... | applications to robotics, autonomy, planning | https://openreview.net/pdf?id=xQRAo9YUQ3 | 2025-09-16T07:58:37 | 4 | [
{
"id": "EwRflc6PT5",
"forum": "xQRAo9YUQ3",
"review_number": 4,
"reviewer_id": "ICLR.cc/2026/Conference/Submission6403/Reviewer_jLCz",
"reviewer_name": "Reviewer_jLCz",
"rating": 4,
"confidence": 4,
"soundness": 3,
"contribution": 2,
"presentation": 3,
"summary": "This p... | |
77VCQs9VSU | https://openreview.net/forum?id=77VCQs9VSU | From Assistants to Companions: Towards the Usefulness of Improving Theory of Mind for Human-AI Symbiosis | 3 | 3 | [
4,
2,
2,
4
] | [
3,
2,
4,
3
] | 4 | [
"Theory of Mind",
"Large Language Model",
"Human-AI Interaction"
] | Theory of Mind (ToM) is crucial for successful human-AI (HAI) interactions. It is a key capability for AI to attribute humans' mental states based on dynamic interactions from a first-person perspective and then improve responses to humans accordingly. However, the existing benchmarks for Large Language Models (LLMs) f... | alignment, fairness, safety, privacy, and societal considerations | https://openreview.net/pdf?id=77VCQs9VSU | 2025-09-19T12:42:30 | 4 | [
{
"id": "ljYTKgnAfU",
"forum": "77VCQs9VSU",
"review_number": 4,
"reviewer_id": "ICLR.cc/2026/Conference/Submission15908/Reviewer_1ry9",
"reviewer_name": "Reviewer_1ry9",
"rating": 4,
"confidence": 3,
"soundness": 3,
"contribution": 3,
"presentation": 3,
"summary": "It pr... | |
0GaCfBRFnf | https://openreview.net/forum?id=0GaCfBRFnf | A Stitch in Time Saves Nine: Proactive Self-Refinement for Language Models | 6 | 3.25 | [
8,
6,
4,
6
] | [
3,
4,
3,
3
] | 4 | [
"Large language models",
"Self-refine"
] | Recent advances in self-refinement have demonstrated significant potential for improving the outputs of large language models (LLMs) through iterative refinement. However, most existing self-refinement methods rely on a reactive process with a fixed number of iterations, making it difficult to determine the optimal tim... | applications to computer vision, audio, language, and other modalities | https://openreview.net/pdf?id=0GaCfBRFnf | 2025-09-19T19:46:35 | 4 | [
{
"id": "ykGVimnysm",
"forum": "0GaCfBRFnf",
"review_number": 4,
"reviewer_id": "ICLR.cc/2026/Conference/Submission17956/Reviewer_RVyM",
"reviewer_name": "Reviewer_RVyM",
"rating": 8,
"confidence": 3,
"soundness": 3,
"contribution": 3,
"presentation": 3,
"summary": "The p... | |
1VCu7aFQzk | https://openreview.net/forum?id=1VCu7aFQzk | Scalable Variational Bayesian Fine-Tuning of LLMs via Orthogonalized Low-Rank Adapter | 3.5 | 4.5 | [
2,
2,
6,
4
] | [
5,
5,
3,
5
] | 4 | [
"Uncertainty Quantification",
"Bayesian Neural Network",
"Bayesian last layer",
"Large Language Models",
"Parameter-Efficient Fine-Tuning",
"Orthogonal Parametrization"
] | When deploying large language models (LLMs) to safety-critical applications, uncertainty quantification (UQ) is of utmost importance to self-assess the reliability of the LLM-based decisions. However, such decisions typically suffer from overconfidence, particularly after parameter-efficient fine-tuning (PEFT) for down... | PoLAR-VBLL combines orthogonalized low-rank adapters with variational Bayesian inference on the last layer to achieve scalable, well-calibrated uncertainty quantification for fine-tuned LLMs while maintaining high accuracy. | probabilistic methods (Bayesian methods, variational inference, sampling, UQ, etc.) | https://openreview.net/pdf?id=1VCu7aFQzk | 2025-09-19T02:37:02 | 4 | [
{
"id": "eguO51Q4I2",
"forum": "1VCu7aFQzk",
"review_number": 4,
"reviewer_id": "ICLR.cc/2026/Conference/Submission13666/Reviewer_XbV5",
"reviewer_name": "Reviewer_XbV5",
"rating": 2,
"confidence": 5,
"soundness": 2,
"contribution": 2,
"presentation": 3,
"summary": "This ... |
qUwOlwao20 | https://openreview.net/forum?id=qUwOlwao20 | TGT: Text-Grounded Trajectories for Locally Controlled Video Generation | 5 | 3.75 | [
4,
4,
6,
6
] | [
4,
3,
4,
4
] | 4 | [
"Text-to-Video Generation; Motion Control"
] | Text-to-video generation has advanced rapidly in visual fidelity, whereas standard methods still have limited ability to control the subject composition of generated scenes. Prior work shows that adding localized text control signals, such as bounding boxes or segmentation masks, can help. However, these methods strugg... | applications to computer vision, audio, language, and other modalities | https://openreview.net/pdf?id=qUwOlwao20 | 2025-09-12T10:16:33 | 4 | [
{
"id": "FuqGmN2Hvh",
"forum": "qUwOlwao20",
"review_number": 4,
"reviewer_id": "ICLR.cc/2026/Conference/Submission4232/Reviewer_TNvT",
"reviewer_name": "Reviewer_TNvT",
"rating": 4,
"confidence": 4,
"soundness": 3,
"contribution": 2,
"presentation": 3,
"summary": "This p... | |
7AlPbFkcs3 | https://openreview.net/forum?id=7AlPbFkcs3 | Semantic Voting: A Self-Evaluation-Free Approach for Efficient LLM Self-Improvement on Unverifiable Open-ended Tasks | 4.5 | 4 | [
6,
2,
6,
4
] | [
4,
4,
4,
4
] | 4 | [
"LLM",
"unsupervised learning",
"self-improvement"
] | The rising cost of acquiring supervised data has driven significant interest in self-improvement for large language models (LLMs). Straightforward unsupervised signals like majority voting have proven effective in generating pseudo-labels for verifiable tasks, while their applicability to unverifiable tasks (e.g., tran... | unsupervised, self-supervised, semi-supervised, and supervised representation learning | https://openreview.net/pdf?id=7AlPbFkcs3 | 2025-09-15T15:19:23 | 4 | [
{
"id": "aprR1WxfnR",
"forum": "7AlPbFkcs3",
"review_number": 4,
"reviewer_id": "ICLR.cc/2026/Conference/Submission5575/Reviewer_nFpD",
"reviewer_name": "Reviewer_nFpD",
"rating": 6,
"confidence": 4,
"soundness": 3,
"contribution": 3,
"presentation": 3,
"summary": "The pa... | |
4LiX5ddGcU | https://openreview.net/forum?id=4LiX5ddGcU | Unified Vision–Language Modeling via Concept Space Alignment | 5.5 | 3.25 | [
4,
6,
6,
6
] | [
4,
4,
2,
3
] | 4 | [
"multimodal embedding space",
"multilingual embedding space"
] | We introduce vSONAR, a vision–language embedding space extended from the text-only embedding space SONAR, which supports 200 text languages and 37 speech languages.
To construct vSONAR, we propose a post-hoc alignment pipeline that maps the representations of an existing vision encoder into the SONAR space.
We thorough... | applications to computer vision, audio, language, and other modalities | https://openreview.net/pdf?id=4LiX5ddGcU | 2025-09-19T00:21:54 | 4 | [
{
"id": "cqGhp46bQk",
"forum": "4LiX5ddGcU",
"review_number": 4,
"reviewer_id": "ICLR.cc/2026/Conference/Submission12990/Reviewer_wU7h",
"reviewer_name": "Reviewer_wU7h",
"rating": 4,
"confidence": 4,
"soundness": 3,
"contribution": 2,
"presentation": 3,
"summary": "This ... | |
4kz4586euw | https://openreview.net/forum?id=4kz4586euw | Simulation-Free Structure Learning for Stochastic Dynamics | 4 | 3.5 | [
4,
2,
2,
8
] | [
3,
4,
4,
3
] | 4 | [
"Structure Learning",
"Trajectory Inference",
"Single-cell",
"Flow Matching",
"Schrödinger Bridge"
] | Modeling dynamical systems and unraveling their underlying causal relationships is central to many domains in the natural sciences. Various physical systems, such as those arising in cell biology, are inherently high-dimensional and stochastic in nature, and admit only partial, noisy state measurements. This poses a si... | We introduce a principled approach for jointly recovering the underlying network structure and dynamic response of a physical system using flow- and score-matching. | applications to physical sciences (physics, chemistry, biology, etc.) | https://openreview.net/pdf?id=4kz4586euw | 2025-09-19T05:09:06 | 4 | [
{
"id": "wcXI5TLFe9",
"forum": "4kz4586euw",
"review_number": 4,
"reviewer_id": "ICLR.cc/2026/Conference/Submission14176/Reviewer_HiCq",
"reviewer_name": "Reviewer_HiCq",
"rating": 4,
"confidence": 3,
"soundness": 4,
"contribution": 3,
"presentation": 3,
"summary": "This ... |
JkKkquv5lw | https://openreview.net/forum?id=JkKkquv5lw | A Study on PAVE Specification for Learnware | 6 | 1.666667 | [
4,
6,
8
] | [
1,
2,
2
] | 3 | [
"Learnware",
"Model Specification",
"Parameter Vector",
"Learnware Identification",
"Model Capability"
] | The *Learnware* paradigm aims to help users solve machine learning tasks by leveraging existing well-trained models rather than starting from scratch. A learnware comprises a submitted model paired with a *specification* sketching its capabilities. For an open platform with continuously uploaded models, these specifica... | We formalize the Parameter Vector (PAVE) specification, which encodes model capabilities for efficient learnware identification, eliminating costly per-model evaluations and outperforming fine-tuned pre-trained models in limited-data scenarios. | other topics in machine learning (i.e., none of the above) | https://openreview.net/pdf?id=JkKkquv5lw | 2025-09-18T20:28:29 | 3 | [
{
"id": "9oer5wRYaF",
"forum": "JkKkquv5lw",
"review_number": 3,
"reviewer_id": "ICLR.cc/2026/Conference/Submission11415/Reviewer_KAPE",
"reviewer_name": "Reviewer_KAPE",
"rating": 4,
"confidence": 1,
"soundness": 3,
"contribution": 3,
"presentation": 3,
"summary": "The p... |
qEzgXEBLIH | https://openreview.net/forum?id=qEzgXEBLIH | Let Physics Guide Your Protein Flows: Topology-aware Unfolding and Generation | 2 | 4.5 | [
2,
2,
2,
2
] | [
5,
4,
5,
4
] | 4 | [
"Protein Structure Generative Models",
"Structure prediction",
"Physics-informed generative model",
"Flow Matching"
] | Protein structure prediction and folding are fundamental to understanding biology, with recent deep learning advances reshaping the field. Diffusion-based generative models have revolutionized protein design, enabling the creation of novel proteins. However, these methods often neglect the intrinsic physical realism of... | We propose a novel physics-informed generative model for protein backbone structure generation using flow matching | applications to physical sciences (physics, chemistry, biology, etc.) | https://openreview.net/pdf?id=qEzgXEBLIH | 2025-09-07T04:17:17 | 4 | [
{
"id": "z5YBR0n0WR",
"forum": "qEzgXEBLIH",
"review_number": 4,
"reviewer_id": "ICLR.cc/2026/Conference/Submission2670/Reviewer_8kS8",
"reviewer_name": "Reviewer_8kS8",
"rating": 2,
"confidence": 5,
"soundness": 2,
"contribution": 2,
"presentation": 2,
"summary": "PhysFl... |
rkfbUc3kO4 | https://openreview.net/forum?id=rkfbUc3kO4 | TraceFlow: Dynamic 3D Reconstruction of Specular Scenes Driven by Ray Tracing | 5 | 4.25 | [
4,
2,
6,
8
] | [
4,
5,
4,
4
] | 4 | [
"4D Reconstruction; Ray Tracing; Specular"
] | We present TraceFlow, a novel framework for high-fidelity rendering of dynamic specular scenes by addressing two key challenges: precise reflection direction estimation and physically accurate reflection modeling. To achieve this, we propose a Residual Material-Augmented 2D Gaussian Splatting representation that models... | We present TraceFlow, a novel framework for high-fidelity rendering of dynamic specular scenes. | applications to computer vision, audio, language, and other modalities | https://openreview.net/pdf?id=rkfbUc3kO4 | 2025-09-19T23:40:32 | 4 | [
{
"id": "Mq2RsJrdlI",
"forum": "rkfbUc3kO4",
"review_number": 4,
"reviewer_id": "ICLR.cc/2026/Conference/Submission19465/Reviewer_dcZt",
"reviewer_name": "Reviewer_dcZt",
"rating": 4,
"confidence": 4,
"soundness": 2,
"contribution": 2,
"presentation": 2,
"summary": "The p... |
yHxSKM9kdr | https://openreview.net/forum?id=yHxSKM9kdr | IceCache: Memory-Efficient KV-cache Management for Long-Sequence LLMs | 4.666667 | 3.666667 | [
4,
4,
6
] | [
3,
4,
4
] | 3 | [
"LLM Inference; KV-cahce Optimization; Sparse Attention"
] | Key-Value (KV) cache plays a pivotal role in accelerating inference in large language models (LLMs) by storing intermediate attention outputs, thereby avoiding redundant computation during auto-regressive generation. However, the cache's memory footprint scales linearly with sequence length, often resulting in memory b... | generative models | https://openreview.net/pdf?id=yHxSKM9kdr | 2025-09-02T00:46:37 | 3 | [
{
"id": "dfOJQiNstJ",
"forum": "yHxSKM9kdr",
"review_number": 3,
"reviewer_id": "ICLR.cc/2026/Conference/Submission541/Reviewer_SWPZ",
"reviewer_name": "Reviewer_SWPZ",
"rating": 4,
"confidence": 3,
"soundness": 3,
"contribution": 3,
"presentation": 2,
"summary": "This pa... | |
8tDIzHFOx6 | https://openreview.net/forum?id=8tDIzHFOx6 | SPR$^2$Q: Static Priority-based Rectifier Routing Quantization for Image Super-Resolution | 5 | 4.5 | [
4,
6,
6,
4
] | [
4,
4,
5,
5
] | 4 | [
"Image Super-Resolution",
"model quantization",
"adapter routing"
] | Low-bit quantization has achieved significant progress in image super-resolution. However, existing quantization methods show evident limitations in handling the heterogeneity of different components. Particularly under extreme low-bit compression, the issue of information loss becomes especially pronounced. In this wo... | applications to computer vision, audio, language, and other modalities | https://openreview.net/pdf?id=8tDIzHFOx6 | 2025-09-19T12:12:15 | 4 | [
{
"id": "1RmJDO6ly6",
"forum": "8tDIzHFOx6",
"review_number": 4,
"reviewer_id": "ICLR.cc/2026/Conference/Submission15779/Reviewer_jipM",
"reviewer_name": "Reviewer_jipM",
"rating": 4,
"confidence": 4,
"soundness": 3,
"contribution": 2,
"presentation": 2,
"summary": "his p... | |
hGoDq7MIK5 | https://openreview.net/forum?id=hGoDq7MIK5 | On the Effect of Positional Encoding for In-context Learning in Transformers | 4.4 | 3.4 | [
4,
6,
2,
4,
6
] | [
3,
4,
5,
3,
2
] | 5 | [
"Transformer Theory",
"In-context Learning",
"Positional Encoding"
] | Transformer models have demonstrated a remarkable ability to perform a wide range of tasks through in-context learning (ICL), where the model infers patterns from a small number of example prompts provided during inference. However, empirical studies have shown that the effectiveness of ICL can be significantly influen... | interpretability and explainable AI | https://openreview.net/pdf?id=hGoDq7MIK5 | 2025-09-19T23:32:30 | 5 | [
{
"id": "Su8le5juia",
"forum": "hGoDq7MIK5",
"review_number": 5,
"reviewer_id": "ICLR.cc/2026/Conference/Submission19405/Reviewer_DDwu",
"reviewer_name": "Reviewer_DDwu",
"rating": 4,
"confidence": 3,
"soundness": 3,
"contribution": 2,
"presentation": 3,
"summary": "This ... | |
dHz2LBCyTh | https://openreview.net/forum?id=dHz2LBCyTh | Batch and Sequential Unlearning for Neural Networks | 6 | 3.5 | [
6,
8,
4,
6
] | [
3,
4,
4,
3
] | 4 | [
"machine unlearning",
"second-order unlearning"
] | With the increasing deployment of machine learning models trained on personal data, machine unlearning has become crucial for data owners to exercise their "right to be forgotten" and protect their privacy. While model owners can retrain the models without the erased data to achieve this goal, this process is often pro... | alignment, fairness, safety, privacy, and societal considerations | https://openreview.net/pdf?id=dHz2LBCyTh | 2025-09-19T13:35:38 | 4 | [
{
"id": "1cBLUxi6YP",
"forum": "dHz2LBCyTh",
"review_number": 4,
"reviewer_id": "ICLR.cc/2026/Conference/Submission16110/Reviewer_mMKS",
"reviewer_name": "Reviewer_mMKS",
"rating": 6,
"confidence": 3,
"soundness": 3,
"contribution": 2,
"presentation": 3,
"summary": "This ... | |
k7ifkwmsXn | https://openreview.net/forum?id=k7ifkwmsXn | SonicMaster: Towards Controllable All-in-One Music Restoration and Mastering | 5 | 4.5 | [
4,
8,
6,
2
] | [
5,
4,
4,
5
] | 4 | [
"Music Restoration",
"Music Mastering",
"Music Generation",
"Audio Generation"
] | Music recordings often suffer from audio quality issues such as excessive reverberation, distortion, clipping, tonal imbalances, and a narrowed stereo image, especially when created in non-professional settings without specialized equipment or expertise. These problems are typically corrected using separate specialized... | We present SonicMaster, an all-in-one music restoration and mastering model controllable by text prompts which is a first of its kind and defines a new task in the field. | applications to computer vision, audio, language, and other modalities | https://openreview.net/pdf?id=k7ifkwmsXn | 2025-09-18T23:39:50 | 4 | [
{
"id": "3ZYuoYPTEr",
"forum": "k7ifkwmsXn",
"review_number": 4,
"reviewer_id": "ICLR.cc/2026/Conference/Submission12745/Reviewer_BVLP",
"reviewer_name": "Reviewer_BVLP",
"rating": 4,
"confidence": 5,
"soundness": 2,
"contribution": 2,
"presentation": 4,
"summary": "The p... |
8HvWBamUkS | https://openreview.net/forum?id=8HvWBamUkS | Adaptive Curriculum Learning for RLHF with Influence-Based Cluster Bandits | 5 | 3.75 | [
4,
6,
4,
6
] | [
3,
4,
4,
4
] | 4 | [
"RLHF",
"Curriculum Learning",
"GRPO"
] | Reinforcement learning (RL) plays a central role in post-training large language models (LLMs). Yet, existing RLHF pipelines typically rely on fixed or uniform sampling strategies, which fail to adapt to the model’s evolving learning state. This mismatch leads to wasted computation on less informative samples while neg... | reinforcement learning | https://openreview.net/pdf?id=8HvWBamUkS | 2025-09-18T21:56:25 | 4 | [
{
"id": "st94h7Dsx7",
"forum": "8HvWBamUkS",
"review_number": 4,
"reviewer_id": "ICLR.cc/2026/Conference/Submission11782/Reviewer_2YAE",
"reviewer_name": "Reviewer_2YAE",
"rating": 4,
"confidence": 3,
"soundness": 2,
"contribution": 2,
"presentation": 2,
"summary": "The p... | |
hAHbo4EGQY | https://openreview.net/forum?id=hAHbo4EGQY | From Masks to Worlds: A Hitchhiker’s Guide to World Models | 3.5 | 3.5 | [
6,
0,
4,
4
] | [
3,
3,
4,
4
] | 4 | [
"World Models",
"Position Paper"
] | This is not a typical survey of world models, it is a guide for those who want to build worlds. We do not aim to catalog every paper that has ever mentioned a ``world model". Instead, we follow one clear road: from early masked models that unified representation learning across modalities, to unified architectures that... | other topics in machine learning (i.e., none of the above) | https://openreview.net/pdf?id=hAHbo4EGQY | 2025-09-08T14:55:55 | 5 | [
{
"id": "mGcAz8i7WC",
"forum": "hAHbo4EGQY",
"review_number": 4,
"reviewer_id": "ICLR.cc/2026/Conference/Submission2999/Reviewer_TWe8",
"reviewer_name": "Reviewer_TWe8",
"rating": 6,
"confidence": 3,
"soundness": 3,
"contribution": 3,
"presentation": 2,
"summary": "This i... | |
mYzlRNMAxS | https://openreview.net/forum?id=mYzlRNMAxS | Why Attention Fails: The Degeneration of Transformers into MLPs in Time Series Forecasting | 4.5 | 3.75 | [
6,
6,
4,
2
] | [
4,
4,
3,
4
] | 4 | [
"Deep Learning",
"Time Series",
"Transformer",
"Degeneration"
] | Transformer-based architectures achieved high performance in natural language processing and computer vision, yet many studies have shown that they have not demonstrated a clear advantage in time series forecasting and even underperform simple linear baselines in some cases. However, most of these studies have not thor... | learning on time series and dynamical systems | https://openreview.net/pdf?id=mYzlRNMAxS | 2025-09-20T09:21:25 | 4 | [
{
"id": "GxeG5thR0A",
"forum": "mYzlRNMAxS",
"review_number": 4,
"reviewer_id": "ICLR.cc/2026/Conference/Submission22455/Reviewer_urWk",
"reviewer_name": "Reviewer_urWk",
"rating": 6,
"confidence": 4,
"soundness": 3,
"contribution": 3,
"presentation": 3,
"summary": "The p... | |
xn9fS09Yir | https://openreview.net/forum?id=xn9fS09Yir | Can Large Language Models Truly Stay Helpful Harmless and Honest? | 4.5 | 2.75 | [
4,
2,
6,
6
] | [
2,
4,
2,
3
] | 4 | [
"LLM",
"Alignment",
"NLP"
] | Alignment of Large Language Models (LLMs) along multiple objectives—helpfulness, harmlessness, and honesty (HHH)—is critical for safe and reliable deployment. Prior work has used steering vectors—small control signals injected into hidden states—to guide LLM outputs, typically via one-to-one (1-to-1) Transformer decode... | alignment, fairness, safety, privacy, and societal considerations | https://openreview.net/pdf?id=xn9fS09Yir | 2025-09-20T14:48:22 | 4 | [
{
"id": "tnxKOi1HIA",
"forum": "xn9fS09Yir",
"review_number": 4,
"reviewer_id": "ICLR.cc/2026/Conference/Submission23963/Reviewer_Tgs7",
"reviewer_name": "Reviewer_Tgs7",
"rating": 4,
"confidence": 2,
"soundness": 2,
"contribution": 2,
"presentation": 1,
"summary": "The p... | |
6zNODYRJvI | https://openreview.net/forum?id=6zNODYRJvI | Reshape-then-Factorize: Communication-Efficient FL via Model-Agnostic Projection Optimization | 4 | 4 | [
4,
2,
4,
6
] | [
4,
5,
3,
4
] | 4 | [
"Federated Learning",
"Low-Rank Adaptation",
"Communication Efficiency",
"Subspace Optimization"
] | Federated learning (FL) enables collaborative model training across distributed clients without sharing sensitive data. However, communication overhead remains a significant bottleneck, particularly for large-scale models. Low-rank decomposition techniques address this by approximating each layer’s weights or gradients... | optimization | https://openreview.net/pdf?id=6zNODYRJvI | 2025-09-19T04:10:01 | 4 | [
{
"id": "1ISa3vX9rA",
"forum": "6zNODYRJvI",
"review_number": 4,
"reviewer_id": "ICLR.cc/2026/Conference/Submission13968/Reviewer_zkJ3",
"reviewer_name": "Reviewer_zkJ3",
"rating": 4,
"confidence": 4,
"soundness": 3,
"contribution": 3,
"presentation": 3,
"summary": "The p... | |
GfPwZwZ9xZ | https://openreview.net/forum?id=GfPwZwZ9xZ | VLASim: World Modelling via VLM-Directed Abstraction and Simulation from a Single Image | 4.5 | 3.5 | [
4,
6,
6,
2
] | [
4,
3,
3,
4
] | 4 | [
"world models",
"video models",
"physical simulation",
"code generation"
] | Generative video models, a leading approach to world modeling, face fundamental limitations. They often violate physical and logical rules, lack interactivity, and operate as opaque black boxes ill-suited for building structured, queryable worlds. To overcome these challenges, we propose a new paradigm focused on disti... | applications to computer vision, audio, language, and other modalities | https://openreview.net/pdf?id=GfPwZwZ9xZ | 2025-09-18T23:57:37 | 4 | [
{
"id": "dVYk98ztUR",
"forum": "GfPwZwZ9xZ",
"review_number": 4,
"reviewer_id": "ICLR.cc/2026/Conference/Submission12870/Reviewer_nHoT",
"reviewer_name": "Reviewer_nHoT",
"rating": 4,
"confidence": 4,
"soundness": 2,
"contribution": 2,
"presentation": 3,
"summary": "The p... | |
5EKDKjNP6P | https://openreview.net/forum?id=5EKDKjNP6P | Beyond Taylor Expansion: Intermediate Activation Perspectives in Structured Pruning | 4 | 4 | [
4,
4,
4
] | [
4,
4,
4
] | 3 | [
"Large Language Model Pruning",
"Large Language Model Compression"
] | Extensive prior work on importance-based pruning relies on first- or second-order Taylor expansions of the loss to score parameters by the estimated loss increase upon removal. However, in large language models with massive parameters and multi-layered nonlinear mappings, such approximations inevitably lead to errors. ... | foundation or frontier models, including LLMs | https://openreview.net/pdf?id=5EKDKjNP6P | 2025-09-18T15:17:05 | 3 | [
{
"id": "LzWSBTZPtp",
"forum": "5EKDKjNP6P",
"review_number": 3,
"reviewer_id": "ICLR.cc/2026/Conference/Submission10696/Reviewer_QEZ6",
"reviewer_name": "Reviewer_QEZ6",
"rating": 4,
"confidence": 4,
"soundness": 2,
"contribution": 2,
"presentation": 2,
"summary": "The p... | |
OUQ8kLRK3m | https://openreview.net/forum?id=OUQ8kLRK3m | Truly Assessing Fluid Intelligence of Large Language Models through Dynamic Reasoning Evaluation | 4 | 3.75 | [
6,
2,
2,
6
] | [
3,
5,
4,
3
] | 4 | [
"Dynamic Reasoning Evaluation",
"Fluid Intelligence",
"Cognition-Inspired Level",
"Various Complexity"
] | Recent advances in large language models (LLMs) have demonstrated impressive reasoning capacities that mirror human-like thinking. However, whether LLMs possess genuine fluid intelligence (i.e., the ability to reason abstractly and generalize rules in novel situations) remains an open question. Existing reasoning bench... | datasets and benchmarks | https://openreview.net/pdf?id=OUQ8kLRK3m | 2025-09-15T15:35:09 | 4 | [
{
"id": "whNtuT6G1Z",
"forum": "OUQ8kLRK3m",
"review_number": 4,
"reviewer_id": "ICLR.cc/2026/Conference/Submission5591/Reviewer_cJQv",
"reviewer_name": "Reviewer_cJQv",
"rating": 6,
"confidence": 3,
"soundness": 3,
"contribution": 3,
"presentation": 3,
"summary": "This w... | |
SX9A72RPU3 | https://openreview.net/forum?id=SX9A72RPU3 | Structured covariance estimation via tensor-train decomposition | 4.5 | 3.25 | [
4,
4,
8,
2
] | [
4,
3,
3,
3
] | 4 | [
"covariance estimation",
"tensor train",
"dimension-free bounds",
"concentration",
"Kronecker product",
"CANDECOMP/PARAFAC"
] | We consider a problem of covariance estimation from a sample of i.i.d. high-dimensional random vectors. To avoid the curse of dimensionality, we impose an additional assumption on the structure of the covariance matrix $\Sigma$. To be more precise, we study the case when $\Sigma$ can be approximated by a sum of double ... | Structured covariance estimation with dimension-free concentration bounds | learning theory | https://openreview.net/pdf?id=SX9A72RPU3 | 2025-09-19T04:18:07 | 4 | [
{
"id": "y5Bgnym4Uw",
"forum": "SX9A72RPU3",
"review_number": 4,
"reviewer_id": "ICLR.cc/2026/Conference/Submission14001/Reviewer_43Kt",
"reviewer_name": "Reviewer_43Kt",
"rating": 4,
"confidence": 4,
"soundness": 4,
"contribution": 2,
"presentation": 3,
"summary": "The p... |
IAFwK6NyrP | https://openreview.net/forum?id=IAFwK6NyrP | The Counting Power of Transformers | 6.4 | 3.8 | [
8,
4,
8,
4,
8
] | [
4,
4,
4,
3,
4
] | 5 | [
"FLaNN",
"expressiveness",
"attention",
"formal languages"
] | Counting properties (e.g. determining whether certain tokens occur more
than other tokens in a given input text) have played a significant role in
the study of expressiveness of transformers.
In this paper, we provide a formal
framework for investigating the counting power of transformers. We argue
... | Transformers can express highly nonlinear counting properties | other topics in machine learning (i.e., none of the above) | https://openreview.net/pdf?id=IAFwK6NyrP | 2025-09-20T02:25:03 | 5 | [
{
"id": "Yf1xZImhqm",
"forum": "IAFwK6NyrP",
"review_number": 5,
"reviewer_id": "ICLR.cc/2026/Conference/Submission20452/Reviewer_sqAV",
"reviewer_name": "Reviewer_sqAV",
"rating": 8,
"confidence": 4,
"soundness": 3,
"contribution": 4,
"presentation": 4,
"summary": "This ... |
GLELajHnCo | https://openreview.net/forum?id=GLELajHnCo | GAPrune: Gradient-Alignment Pruning for Domain-Aware Embeddings | 4 | 3.333333 | [
4,
2,
6
] | [
3,
4,
3
] | 3 | [
"Embedding Model; Domain Adaptation; Domain Pruning"
] | Domain-specific embedding models have shown promise for applications that require specialized semantic understanding, such as coding agents and financial retrieval systems, often achieving higher performance gains than general models. However, state-of-the-art embedding models are typically based on LLMs, which contain... | GAPrune prunes embedding models using domain-general gradient alignment, achieving 50% sparsity while enhancing domain performance. | other topics in machine learning (i.e., none of the above) | https://openreview.net/pdf?id=GLELajHnCo | 2025-09-13T16:00:31 | 3 | [
{
"id": "LvM5UZeuQc",
"forum": "GLELajHnCo",
"review_number": 3,
"reviewer_id": "ICLR.cc/2026/Conference/Submission4705/Reviewer_nY2B",
"reviewer_name": "Reviewer_nY2B",
"rating": 4,
"confidence": 3,
"soundness": 2,
"contribution": 2,
"presentation": 2,
"summary": "The au... |
BwjNHzwAOq | https://openreview.net/forum?id=BwjNHzwAOq | Introducing Multimodal Paradigm for Learning Sleep Staging PSG via General-purpose Model | 5.2 | 4 | [
6,
2,
4,
8,
6
] | [
4,
4,
4,
4,
4
] | 5 | [
"Physiological Signal Processing",
"Sleep Staging",
"Brain Computer Interfaces",
"Interpretable AI"
] | Sleep staging is essential for diagnosing sleep disorders and assessing neurological health. Existing automatic methods typically extract features from complex polysomnography (PSG) signals and train domain-specific models, which often lack intuitiveness and require large, specialized datasets. To overcome these limita... | applications to neuroscience & cognitive science | https://openreview.net/pdf?id=BwjNHzwAOq | 2025-09-15T15:15:43 | 5 | [
{
"id": "DJp584LumL",
"forum": "BwjNHzwAOq",
"review_number": 5,
"reviewer_id": "ICLR.cc/2026/Conference/Submission5571/Reviewer_xaDv",
"reviewer_name": "Reviewer_xaDv",
"rating": 6,
"confidence": 4,
"soundness": 4,
"contribution": 3,
"presentation": 3,
"summary": "This p... | |
R0JM3BWP7W | https://openreview.net/forum?id=R0JM3BWP7W | Tricks or Traps? A Deep Dive into RL for LLM Reasoning | 6 | 3.5 | [
8,
4,
6,
6
] | [
4,
4,
3,
3
] | 4 | [
"Large Language Models Reasoning; Reinforcement Learning; Reasoning"
] | Reinforcement learning (RL) for LLM reasoning has rapidly emerged as a prominent research area, marked by a significant surge in related studies on both algorithmic innovations and practical applications. Despite this progress, several critical challenges remain, including the absence of standardized guidelines for app... | foundation or frontier models, including LLMs | https://openreview.net/pdf?id=R0JM3BWP7W | 2025-09-19T16:57:07 | 4 | [
{
"id": "rUBWurzab4",
"forum": "R0JM3BWP7W",
"review_number": 4,
"reviewer_id": "ICLR.cc/2026/Conference/Submission17104/Reviewer_rKt2",
"reviewer_name": "Reviewer_rKt2",
"rating": 8,
"confidence": 4,
"soundness": 3,
"contribution": 3,
"presentation": 3,
"summary": "This ... | |
KdYKSOY9MP | https://openreview.net/forum?id=KdYKSOY9MP | Cosmos-Eval: Towards Explainable Evaluation of Physics and Semantics in Text-to-Video Models | 4.5 | 3.25 | [
4,
4,
4,
6
] | [
4,
3,
3,
3
] | 4 | [
"Cosmos-Eval",
"Explainable Evaluation"
] | Recent text-to-video (T2V) models have achieved impressive visual fidelity, yet they remain prone to failures in two critical dimensions: adhering to prompt semantics and respecting physical commonsense. Existing benchmarks, including VideoPhy and VideoPhy-2, formalize these axes but provide only scalar scores, leaving... | foundation or frontier models, including LLMs | https://openreview.net/pdf?id=KdYKSOY9MP | 2025-09-19T14:47:13 | 4 | [
{
"id": "LkJozPzECV",
"forum": "KdYKSOY9MP",
"review_number": 4,
"reviewer_id": "ICLR.cc/2026/Conference/Submission16433/Reviewer_JK2k",
"reviewer_name": "Reviewer_JK2k",
"rating": 4,
"confidence": 4,
"soundness": 2,
"contribution": 3,
"presentation": 3,
"summary": "Summa... | |
hABW989AOr | https://openreview.net/forum?id=hABW989AOr | Tensor Power Methods: Faster and Robust for Arbitrary Order | 4.5 | 3.75 | [
6,
4,
4,
4
] | [
5,
3,
4,
3
] | 4 | [
"tensor power method",
"arbitrary order",
"Canonical/Polyadic decomposition"
] | Tensor decomposition is a fundamental method used in various areas to deal with high-dimensional data. Among the widely recognized techniques for tensor decomposition is the Canonical/Polyadic (CP) decomposition, which breaks down a tensor into a combination of rank-1 components. In this paper, we specifically focus on... | optimization | https://openreview.net/pdf?id=hABW989AOr | 2025-09-20T06:37:39 | 4 | [
{
"id": "WdvfbzIgA5",
"forum": "hABW989AOr",
"review_number": 4,
"reviewer_id": "ICLR.cc/2026/Conference/Submission21763/Reviewer_c8NC",
"reviewer_name": "Reviewer_c8NC",
"rating": 6,
"confidence": 5,
"soundness": 3,
"contribution": 3,
"presentation": 2,
"summary": "The p... | |
EPTVoeaz7Y | https://openreview.net/forum?id=EPTVoeaz7Y | RANGER: Repository-Level Agent for Graph Enhanced Retrieval | 2.5 | 4.25 | [
2,
2,
2,
4
] | [
4,
5,
4,
4
] | 4 | [
"GraphRAG",
"Monte Carlo Tree Search",
"Repository-level",
"Retrieval Agent",
"Code Retrieval",
"Retrieval-Augmented Generation",
"Software Engineering",
"Graph Traversal",
"Multi-hop Reasoning",
"Code Search"
] | General-purpose automated software engineering (ASE) includes tasks such as code completion, retrieval, repair, QA, and summarization. These tasks require a code retrieval system that can handle specific queries about code entities, or code entity queries (for example, locating a specific class or retrieving the depend... | other topics in machine learning (i.e., none of the above) | https://openreview.net/pdf?id=EPTVoeaz7Y | 2025-09-20T00:37:36 | 4 | [
{
"id": "2NhWe9GwGm",
"forum": "EPTVoeaz7Y",
"review_number": 4,
"reviewer_id": "ICLR.cc/2026/Conference/Submission19837/Reviewer_eG5f",
"reviewer_name": "Reviewer_eG5f",
"rating": 2,
"confidence": 4,
"soundness": 3,
"contribution": 2,
"presentation": 2,
"summary": "This ... | |
VjtMhU3zWn | https://openreview.net/forum?id=VjtMhU3zWn | SchemaRAG: Enhancing Knowledge-Intensive Reasoning of LLMs via Inference-Time Adaptive Schema | 4.5 | 3.75 | [
6,
4,
4,
4
] | [
4,
4,
4,
3
] | 4 | [
"Knowledge Intensive Reasoning",
"RAG",
"LLM"
] | Retrieval-Augmented Generation (RAG) often struggles with integrating fragmented knowledge for complex reasoning tasks. Recent efforts introduce structural templates—such as graphs or knowledge-based organizations—to improve multi-document reasoning. However, they are constrained by their rigidity, failing to adapt to ... | generative models | https://openreview.net/pdf?id=VjtMhU3zWn | 2025-09-20T16:29:27 | 4 | [
{
"id": "CBhF0GEgRV",
"forum": "VjtMhU3zWn",
"review_number": 4,
"reviewer_id": "ICLR.cc/2026/Conference/Submission24445/Reviewer_Vc2h",
"reviewer_name": "Reviewer_Vc2h",
"rating": 6,
"confidence": 4,
"soundness": 3,
"contribution": 2,
"presentation": 2,
"summary": "The p... |
Subsets and Splits
ICLR 2026 Papers with CAD
Performs basic pattern matching to find records containing "cad" in the title, providing simple filtered results but offering minimal analytical insight into the dataset's broader patterns or relationships.
ICLR 2026 Papers with CAD
Performs basic pattern matching to find records containing "cad" in the title, providing simple filtered results but offering limited analytical insight.