1 citations · 1 across the 5 of their papers we have counts for
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…
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…
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…
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…
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…