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Xiangning Yu

2 accepted papers

2025

Causal Sufficiency and Necessity Improves Chain-of-Thought Reasoning

NeurIPS 2025poster

Chain-of-Thought (CoT) prompting plays an indispensable role in endowing large language models (LLMs) with complex reasoning capabilities. However, CoT currently faces two fundamental challenges: (1) Sufficiency, which ensures that the generated intermediate inference steps comprehensively cover and…

Cited by 0SourceScholar
2025

MF-LLM: Simulating Population Decision Dynamics via a Mean-Field Large Language Model Framework

NeurIPS 2025poster

Simulating collective decision-making involves more than aggregating individual behaviors; it emerges from dynamic interactions among individuals. While large language models (LLMs) offer strong potential for social simulation, achieving quantitative alignment with real-world data remains a key chal…

Cited by 0SourcecodeScholar