Papers by Weiwei LI

1 papers
Mixture-of-Minds: Multi-Agent Reinforcement Learning for Table Understanding (2026.acl-long)

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Challenge: Large language models (LLMs) have shown promise on understanding and reasoning over tables, but current approaches remain limited.
Approach: They propose a multi-agent framework that decomposes table reasoning into three specialized roles: planning, coding, and answering.
Outcome: The proposed framework decomposes table reasoning into three specialized roles: planning, coding, and answering.

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