Papers by Chanhwi Kim
ToxReason: A Benchmark for Mechanistic Chemical Toxicity Reasoning via Adverse Outcome Pathway (2026.findings-acl)
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| Challenge: | Recent advances in large language models have enabled molecular reasoning for property prediction. however, toxicity arises from complex biological mechanisms, necessitating mechanistic reasoning for reliable prediction. |
| Approach: | They propose a benchmark that evaluates organ-level toxicity reasoning across multiple organs . they find strong predictive performance does not necessarily imply reliable reasoning . |
| Outcome: | The proposed benchmark evaluates toxicity prediction performance and reasoning quality across LLMs. |
Learning from Negative Samples in Biomedical Generative Entity Linking (2025.findings-acl)
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| Challenge: | Generative models are usually trained only with positive samples and do not explicitly learn from hard negative samples, which are entities that look similar but have different meanings. |
| Approach: | They propose a framework that trains generative BioEL models using negative samples to learn from hard negative samples. |
| Outcome: | The proposed framework outperforms baseline models by up to an average top-1 accuracy of 1.4% on five benchmarks. |
Aspect-Oriented Summarization for Psychiatric Short-Term Readmission Prediction (2025.emnlp-main)
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WonJin Yoon, Boyu Ren, Spencer Thomas, Chanhwi Kim, Guergana K Savova, Mei-Hua Hall, Timothy A. Miller
| Challenge: | Recent advances in large language models have enabled the automated processing of lengthy documents even without supervised training on a task-specific dataset. |
| Approach: | They propose a method for processing the summaries of long documents using different aspect-oriented prompts and integrate the information signals from these different prompts for supervised training of transformer models. |
| Outcome: | The proposed method improves on a high-impact task predicting readmissions from a psychiatric discharge using real-world data from four hospitals. |