Papers by Christophe Ye

3 papers
LLM as Entity Disambiguator for Biomedical Entity-Linking (2025.acl-short)

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Challenge: Entity linking involves normalizing a mention in medical text to a unique identifier in a knowledge base, such as UMLS or MeSH.
Approach: They propose to use a large language model as an entity disambiguator to enhance the accuracy of alias-matching entity linking methods.
Outcome: The proposed method surpasses existing methods on biomedical datasets by up to 16 points in accuracy.
Where do LLMs currently stand on biomedical NER in both clean and noisy settings ? (2026.findings-eacl)

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Challenge: despite advances in medicine, many diseases remain without effective treatments . clinical meta-analysis is essential for drug discovery and clinical research .
Approach: They investigate the performance of large language models (LLMs) on biomedical NER tasks . findings suggest LLMs exhibit a notable degree of robustness to noise .
Outcome: The proposed models are closing the performance gap with BERT-based models and demonstrate particular strengths in low-data settings.
BioEL: A Comprehensive Python Package for Biomedical Entity Linking (2025.findings-naacl)

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Challenge: Entity Linking in biomedical literature is a critical task that enhances the extraction and integration of information from diverse scientific literature.
Approach: They propose a Python package that allows for better Entity Linking in biomedical literature . the package includes four components: Ontology Object, Dataset Object and Evaluation Framework .
Outcome: The proposed open-source package enables the implementation and comparison of biomedical entity linking tasks.

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