AnyJev

Training-free Jev-style typed decisions from LLM next-token probabilities. L0 uses cyclic option rotations and label-prior correction to reduce bias without labels; L1 fits temperature calibration using labeled examples. No base-model fine-tuning; calibration and order stability are not universal guarantees.

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