5 papers
Ryze: Evidence-Enriched Data Synthesis from Biomedical Papers
Yeqi Huang, Yue Chen, Yanwei Ye +2
General-purpose VLMs remain unreliable for biomedical research because valid answers in scientific papers depend on evidence split across figures, tables, charts, captions, and ref…
Distilling Counterfactual Reasoning from Language to Vision: Causal Graph Guided Post-Training for Video Understanding
Yuefei Chen, Jiang Liu, Xiaodong Lin +1
Vision Language Models (VLMs) have recently shown significant advancements in video understanding, especially in feature alignment, event reasoning, and instruction-following tasks…
Where Fake Citations Are Made: Tracing Field-Level Hallucination to Specific Neurons in LLMs
Yuefei Chen, Yihao Quan, Xiaodong Lin +1
LLMs frequently generate fictitious yet convincing citations, often expressing high confidence even when the underlying reference is wrong. We study this failure across 9 models an…
CounterBench: Evaluating and Improving Counterfactual Reasoning in Large Language Models
Yuefei Chen, Vivek K. Singh, Jing Ma +1
Counterfactual reasoning is widely recognized as one of the most challenging and intricate aspects of causality in artificial intelligence. In this paper, we evaluate the performan…
Topology of Reasoning: Retrieved Cell Complex-Augmented Generation for Textual Graph Question Answering
Sen Zhao, Lincheng Zhou, Yue Chen +1
Retrieval-Augmented Generation (RAG) enhances the reasoning ability of Large Language Models (LLMs) by dynamically integrating external knowledge, thereby mitigating hallucinations…