Papers by Hariprasad Reddy Korsapati
Process-Supervised Reward Models for Verifying Clinical Note Generation: A Scalable Approach Guided by Domain Expertise (2025.emnlp-main)
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Hanyin Wang, Chufan Gao, Qiping Xu, Bolun Liu, Guleid Hussein, Hariprasad Reddy Korsapati, Mohamad El Labban, Kingsley Iheasirim, Mohamed Hassan, Gokhan Anil, Brian Bartlett, Jimeng Sun
| Challenge: | Currently, no automated, scalable method exists to evaluate the quality of LLM-generated clinical notes, leaving manual evaluation the gold standard. |
| Approach: | They propose a framework for training PRMs to deliver step-level reward signals for LLM-generated clinical notes. |
| Outcome: | The proposed framework outperforms reasoning and non-reasoning models on key evaluations and selects physician-preferred clinical notes with 56.2% accuracy. |
Towards Adapting Open-Source Large Language Models for Expert-Level Clinical Note Generation (2025.findings-acl)
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Hanyin Wang, Chufan Gao, Bolun Liu, Qiping Xu, Guleid Hussein, Mohamad El Labban, Kingsley Iheasirim, Hariprasad Reddy Korsapati, Chuck Outcalt, Jimeng Sun
| Challenge: | Proprietary Large Language Models (LLMs) have demonstrated promising capabilities in clinical text summarization tasks. |
| Approach: | They propose a domain- and task-specific adaptation process for an open-source LLaMA-2 model . LLama-2 can generate high-quality clinical notes from outpatient patient-doctor dialogues . |
| Outcome: | The proposed model can generate clinical notes comparable to those authored by physicians. |