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Zhengyuan Pan

2 accepted papers

2026

Prototype Entropy Alignment: Reinforcing Structured Uncertainty in LLM Reasoning

AAAI 2026technical

Recent research reveals that a minority of high-entropy tokens significantly influence the reasoning quality of large language models (LLMs). Inspired by this, we propose Prototype Entropy Alignment (PEA), a reinforcement learning framework that models effective reasoning not as a single path but as

Cited by 0SourcePDFScholar
2025

Enhancing Information Extraction with METORIE: A Metaphor and Trap-Based Dataset for Cross-Domain Fine-Tuning

ICASSP 2025accepted

This research proposes the METORIE dataset <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</sup>, a novel resource designed to improve the reasoning capabilities of large language models (LLMs), such as LLaMA3 and GLM4, in information extraction (IE)…

Cited by 0SourceScholar