Papers by Chenkang Zhang

2 papers
Intriguing Effect of the Correlation Prior on ICD-9 Code Assignment (2023.acl-srw)

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Challenge: The Ninth Revision of the International Classification of Diseases (ICD-9) is a standardized coding system used worldwide to classify and code diseases, injuries, and other health conditions.
Approach: They evaluate the usefulness of correlation bias and suggest it could improve ICD-9 code assignment in some cases.
Outcome: The proposed model improves on classes that are more imbalanced and less correlated with other codes, but the effect on individual class can be negative or positive.
CaDRL: Document-level Relation Extraction via Context-aware Differentiable Rule Learning (2025.coling-main)

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Challenge: Existing methods for document-level relation extraction (DocRE) lack logic and transparency.
Approach: They propose a Context-aware differentiable rule learning framework that learns the doc-specific logical rule to avoid suboptimal constraints.
Outcome: The proposed framework outperforms existing rule-based frameworks on three DocRE datasets.

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