Papers by Wenjun Feng

1 papers
Eval-RAR: Evaluation-Driven Retrieval-Augmented Reasoning via Reinforcement Learning (2026.findings-acl)

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Challenge: Existing methods for retrieval-augmented generation fail to provide explicit supervision for internal reasoning process.
Approach: They propose an Evaluation-driven Retrieval-Augmented Reasoning framework that uses reinforcement learning and a fine-grained evaluation reward to optimize the process.
Outcome: Eval-RAR outperforms existing methods on QA benchmarks on seven single-hop and multi-hop tasks.

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