3 papers
cs.CL2026
A Training-Free Regeneration Paradigm: Contrastive Reflection Memory Guided Self-Verification and Self-Improvement
Yuran Li, Di Wu, Benoit Boulet
Verification-guided self-improvement has recently emerged as a promising approach to improving the accuracy of large language model (LLM) outputs. However, existing approaches face…
cs.AI2025
Leveraging LLMs as Meta-Judges: A Multi-Agent Framework for Evaluating LLM Judgments
Yuran Li, Jama Hussein Mohamud, Chongren Sun +2
Large language models (LLMs) are being widely applied across various fields, but as tasks become more complex, evaluating their responses is increasingly challenging. Compared to h…
cs.CL2025
OnionEval: An Unified Evaluation of Fact-conflicting Hallucination for Small-Large Language Models
Chongren Sun, Yuran Li, Di Wu +1
Large Language Models (LLMs) are highly capable but require significant computational resources for both training and inference. Within the LLM family, smaller models (those with f…