Papers by Shijing Chen

1 papers
Leveraging Taxonomy and LLMs for Improved Multimodal Hierarchical Classification (2025.coling-main)

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Challenge: Multi-level Hierarchical Classification (MLHC) is a critical tool in modern data analysis.
Approach: They propose a taxonomy-embedded transitional LLM-agnostic framework for multimodality classification that leverages large language models to enforce consistency across hierarchical levels.
Outcome: The proposed framework improves on the MEP-3M dataset with various hierarchical levels compared to conventional models.

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