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Multimodal Chemical Structure-Text Coreference in Intellectual Property via Rule-guided Reinforcement Learning (2026.findings-acl)

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Challenge: Existing tools for identifying chemical structures and textual referents are inadequate for this multimodal task.
Approach: They propose a RULE-guided multimodal Reinforcement learning framework for chemical structure-text coreference . RULER is a rule-driven reinforcement learning framework that uses rule-based reward functions to obtain the correct domain knowledge.
Outcome: The proposed framework improves on the baseline framework and shows superior efficacy.

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