LoopCD: Loop-wise Contrastive Decoding for Improving Reasoning in Looped Language Models
LoopCD, loop-wise contrastive decoding that enhances the reasoning performance of LoopLMs by intervening on these tokens at inference time by exploiting the internal dynamics of LoopLMs and contrast the logits from earlier iterations with logits from the last refined iteration to form the final sampling distribution.
Byeongho Yu, Junhyuk So, Eunhyeok Park
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