Papers by Chuyue Zhou

2 papers
INFORM : Information eNtropy based multi-step reasoning FOR large language Models (2023.emnlp-main)

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Challenge: Large language models (LLMs) have demonstrated exceptional performance with dedicated Chain-of-Thought (CoT) prompts.
Approach: They propose a new method by introducing information entropy as a criteria on for CoT prompt selection.
Outcome: The proposed model outperforms existing models on seven reasoning benchmarks using two language models.
ALW: Adaptive Layer-Wise contrastive decoding enhancing reasoning ability in Large Language Models (2025.findings-acl)

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Challenge: Existing research has demonstrated that contrast decoding of two different models can improve text quality in open-ended text generation but with limited gains on reasoning tasks.
Approach: They propose a framework that dynamically disentangles noise in shallow layers from critical signals in deep layers to enhance reasoning ability.
Outcome: The proposed framework improves answer accuracy while maintaining inference efficiency.

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