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Shenzhen University
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Distinguishing negative samples can boost LLM reasoning performance on ARC-like tasks by providing critical near-miss alternatives.
Forget fine-tuning: DeCoVec steers LLMs to better accuracy (+5.5% on average) by simply nudging the decoding logits based on in-context learning.
