Papers by Zhinan Gou

1 papers
UR2 : Unify RAG and Reasoning through Reinforcement Learning (2026.acl-long)

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Challenge: Existing attempts to unify large language models are limited to open-domain QA with fixed retrieval settings.
Approach: They propose a general reinforcement learning framework that dynamically coordinates retrieval and reasoning.
Outcome: The proposed framework outperforms existing paradigms on open-domain QA, MMLU-Pro, medical, and mathematical reasoning tasks.

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