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Layer-Order Inversion: Rethinking Latent Multi-Hop Reasoning in Large Language Models
Xukai Liu, Ye Liu, Jipeng Zhang +3
Large language models (LLMs) perform well on multi-hop reasoning, yet how they internally compose multiple facts remains unclear. Recent work proposes \emph{hop-aligned circuit hyp…
RIDE: Difficulty Evolving Perturbation with Item Response Theory for Mathematical Reasoning
Xinyuan Li, Murong Xu, Wenbiao Tao +4
Large language models (LLMs) achieve high performance on mathematical reasoning, but these results can be inflated by training data leakage or superficial pattern matching rather t…
MARS-SQL: A multi-agent reinforcement learning framework for Text-to-SQL
Haolin Yang, Jipeng Zhang, Zhitao He +2
Large Language Models (LLMs) often struggle with the precise logic and schema alignment required for complex Text-to-SQL tasks. While current methods rely heavily on static prompti…
Med-RewardBench: Benchmarking Reward Models and Judges for Medical Multimodal Large Language Models
Meidan Ding, Jipeng Zhang, Wenxuan Wang +6
Multimodal large language models (MLLMs) hold significant potential in medical applications, including disease diagnosis and clinical decision-making. However, these tasks require…
VL-GenRM: Enhancing Vision-Language Verification via Vision Experts and Iterative Training
Jipeng Zhang, Kehao Miao, Renjie Pi +4
Reinforcement Fine-Tuning (RFT) with verifiable rewards has advanced large language models but remains underexplored for Vision-Language (VL) models. The Vision-Language Reward Mod…
Benchmarking Multi-National Value Alignment for Large Language Models
Weijie Shi, Chengyi Ju, Chengzhong Liu +8
Do Large Language Models (LLMs) hold positions that conflict with your country's values? Occasionally they do! However, existing works primarily focus on ethical reviews, failing t…