5 papers · 1 filter
SIREN: Towards End-to-End Extreme-Weather Early Warning with Experience-Grounded LLM Agents
Hang Ni, Weijia Zhang, Fan Liu +2
Early warning of extreme weather is essential for mitigating the societal, economic, and environmental risks posed by hazardous weather events. However, expert-centered warning wor…
DSWorld: A Data Science World Model for Efficient Autonomous Agents
Zherui Yang, Fan Liu, Hao Liu
Despite strong capabilities in data understanding and decision-making, autonomous data science agents still heavily rely on trial-and-error workflows that involve expensive computa…
EvoDS: Self-Evolving Autonomous Data Science Agent with Skill Learning and Context Management
Zherui Yang, Fan Liu, Yansong Ning +1
Recent progress in Large Language Model (LLM) agents has enabled promising advances in automated data science. However, existing approaches remain fundamentally limited by their st…
MM-Agent: LLM as Agents for Real-world Mathematical Modeling Problem
Fan Liu, Zherui Yang, Cancheng Liu +3
Mathematical modeling is a cornerstone of scientific discovery and engineering practice, enabling the translation of real-world problems into formal systems across domains such as…
Bag of Tricks for Inference-time Computation of LLM Reasoning
Fan Liu, Wenshuo Chao, Naiqiang Tan +1
With the advancement of large language models (LLMs), solving complex reasoning tasks has gained increasing attention. Inference-time computation methods (e.g., Best-of-N, beam sea…