3 papers
cs.CV2025
CauSight: Learning to Supersense for Visual Causal Discovery
Yize Zhang, Meiqi Chen, Sirui Chen +4
Causal thinking enables humans to understand not just what is seen, but why it happens. To replicate this capability in modern AI systems, we introduce the task of visual causal di…
cs.CL2025
Synergizing Large Language Models and Theory for Human-like Causal Reasoning
Yanxi Zhang, Xin Cong, Zhong Zhang +3
Performing causal reasoning akin to humans is fundamental to achieving strong artificial intelligence. However, existing studies on causal reasoning and large language models (LLMs…
cs.CL2023
From Simple to Complex: A Progressive Framework for Document-level Informative Argument Extraction
Quzhe Huang, Yanxi Zhang, Dongyan Zhao
Document-level Event Argument Extraction (EAE) requires the model to extract arguments of multiple events from a single document. Considering the underlying dependencies between th…