Papers by Jieyang Xu

1 papers
Escaping the Sisyphus Dilemma: Experience Replay for Robust Text-to-Optimization Modeling (2026.findings-acl)

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Challenge: Existing retrieval-augmented strategies for large language models fail to capture dynamic reasoning required to resolve execution failures.
Approach: They propose a framework that implements Experience Replay to transform transient rectification steps into persistent knowledge.
Outcome: The proposed framework improves model accuracy by 8.45% on complex tasks while reducing token consumption by 28.65% and interaction turns by 25.82%.

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