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honey90
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FINAL-Bench/Tetris-JEV-LAYA-ZTC
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The cost of a judging gate is usually quoted as a number. This puts it on a Tetris board. Three boards get the same piece order, and on every move the same proposal and the same noise โ a paired comparison. The gate decides one thing: keep this move, or draw again. Each board gets the same 60 seconds of gate time. The text-writing gates get through 15โ22 moves. The generation-free gate gets through 40โ50. The boards that stop simply run out of clock. It does not win on accuracy: on the same 2,018-question LODO set, JEV scores AUC 0.7350 against ZTC-Judge-27B's 0.7289. The separation is elsewhere. Clock โ 2.1 s vs 0.0615 s per call, and on a 200-candidate agent screen one judging call measured 3.206 s generative vs 0.033 s readout, same server. Calibration โ a gate is a threshold, and at ECE 0.4985 (vs ZTC 0.0245) a threshold stops carrying information. Mechanism โ a text judge can name option 42 when there is no option 42; a scoring readout cannot. Not a lower error rate. No path. The curve in the ZTC panel is real online fitting, scored prequentially โ predict first, learn after โ with base weights untouched. Not recursive self-improvement. Limits, also stated on the page: Laya's AUC and latency are not our measurements and are set equal to JEV's, so calibration is the only measured axis it differs on. The page is a simulation driven by measured constants. KO / EN / ZH. https://huggingface.co/spaces/FINAL-Bench/Tetris-JEV-LAYA-ZTC https://huggingface.co/FINAL-Bench/ZTC-Judge-27B
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Your model already knows it's wrong. Asking costs 0.06 seconds and zero tokens.
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