Papers by Hanmeng Zhong

3 papers
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.
CRAB: A Benchmark for Evaluating Curation of Retrieval-Augmented LLMs in Biomedicine (2025.emnlp-industry)

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Challenge: Recent development in Retrieval-Augmented Large Language Models (LLMs) have shown great promise in biomedical applications.
Approach: They propose a multilingual benchmark to evaluate retrieval-augmented large language models' curation ability.
Outcome: The proposed benchmark is available in English, French, German and Chinese.
The Dominance of Text Space: Unveiling the Asymmetric Nature of Cross-Modal Alignment in Large Language Models (2026.acl-long)

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Challenge: Existing methods for cross-modal alignment assume a symmetric interaction between visual and textual modalities, implying that both spaces adapt to each other.
Approach: They propose a method that regularizes the projector to maintain the geometric structure of the text embedding space via spectral filtering.
Outcome: The proposed method preserves the LLM’s inherent linguistic capabilities and reduces object hallucination significantly better than standard fine-tuning methods.

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