202 citations · 558 across the 43 of their papers we have counts for
5 papers · 1 filter
Interactive Learning for LLM Reasoning
Hehai Lin, Shilei Cao, Sudong Wang +5
Existing multi-agent learning approaches have developed interactive training environments to explicitly promote collaboration among multiple Large Language Models (LLMs), thereby c…
MCEval: A Dynamic Framework for Fair Multilingual Cultural Evaluation of LLMs
Shulin Huang, Linyi Yang, Yue Zhang
Large language models exhibit cultural biases and limited cross-cultural understanding capabilities, particularly when serving diverse global user populations. We propose MCEval, a…
DeepReview: Improving LLM-based Paper Review with Human-like Deep Thinking Process
Minjun Zhu, Yixuan Weng, Linyi Yang +1
Large Language Models (LLMs) are increasingly utilized in scientific research assessment, particularly in automated paper review. However, existing LLM-based review systems face si…
An Empirical Analysis of Uncertainty in Large Language Model Evaluations
Qiujie Xie, Qingqiu Li, Zhuohao Yu +3
As LLM-as-a-Judge emerges as a new paradigm for assessing large language models (LLMs), concerns have been raised regarding the alignment, bias, and stability of LLM evaluators. Wh…
Direct Value Optimization: Improving Chain-of-Thought Reasoning in LLMs with Refined Values
Hongbo Zhang, Han Cui, Guangsheng Bao +3
We introduce Direct Value Optimization (DVO), an innovative reinforcement learning framework for enhancing large language models in complex reasoning tasks. Unlike traditional meth…