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cs.HC2026
MUSE: An Interactive Meta-Agent for Understanding and Steering LLM-powered Data Science Systems
Wei-Hao Chen, Weixi Tong, Yuan Tian +2
Recent advances in large language models have enabled a new class of agentic data science systems that allow users to complete complex data science workflows through natural langua…
cs.CL2026
Explore-on-Graph: Incentivizing Autonomous Exploration of Large Language Models on Knowledge Graphs with Path-refined Reward Modeling
Shiqi Yan, Yubo Chen, Ruiqi Zhou +8
The reasoning process of Large Language Models (LLMs) is often plagued by hallucinations and missing facts in question-answering tasks. A promising solution is to ground LLMs' answ…