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cs.CL2025
Are Large Reasoning Models Good Translation Evaluators? Analysis and Performance Boost
Runzhe Zhan, Zhihong Huang, Xinyi Yang +3
Recent advancements in large reasoning models (LRMs) have introduced an intermediate "thinking" process prior to generating final answers, improving their reasoning capabilities on…
cs.CL2025
Understanding Aha Moments: from External Observations to Internal Mechanisms
Shu Yang, Junchao Wu, Xin Chen +4
Large Reasoning Models (LRMs), capable of reasoning through complex problems, have become crucial for tasks like programming, mathematics, and commonsense reasoning. However, a key…
cs.CL2025★ 1 cited
Rethinking Prompt-based Debiasing in Large Language Models
Xinyi Yang, Runzhe Zhan, Derek F. Wong +3
Investigating bias in large language models (LLMs) is crucial for developing trustworthy AI. While prompt-based through prompt engineering is common, its effectiveness relies on th…