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Zheyuan Xiao

2 accepted papers

2025

Explaining Length Bias in LLM-Based Preference Evaluations

EMNLP 2025

The use of large language models (LLMs) as judges, particularly in preference comparisons, has become widespread, but this reveals a notable bias towards longer responses, undermining the reliability of such evaluations. To better understand such bias, we propose to decompose the preference evaluati

Cited by 0SourcePDFScholar
2025

Unveiling the Learning Mind of Language Models: A Cognitive Framework and Empirical Study

NeurIPS 2025poster

Large language models (LLMs) have shown impressive capabilities across tasks such as mathematics, coding, and reasoning, yet their learning ability, which is crucial for adapting to dynamic environments and acquiring new knowledge, remains underexplored. In this work, we address this gap by introduc…

Cited by 0SourceScholar