Papers by Duo Peng

1 papers
PaperSearchQA: Learning to Search and Reason over Scientific Papers with RLVR (2026.eacl-long)

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Challenge: Recent methods supervise only the final answer accuracy using reinforcement learning with verifiable rewards (RLVR).
Approach: They propose to train search agents to search and reason over scientific papers and a factoid QA dataset with 60k biomedical paper abstracts.
Outcome: The proposed model outperforms non-RL retrieval baselines and is scalable and extendable to other scientific domains.

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