Papers by Sunjun Kweon
Publicly Shareable Clinical Large Language Model Built on Synthetic Clinical Notes (2024.findings-acl)
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Sunjun Kweon, Junu Kim, Jiyoun Kim, Sujeong Im, Eunbyeol Cho, Seongsu Bae, Jungwoo Oh, Gyubok Lee, Jong Hak Moon, Seng Chan You, Seungjin Baek, Chang Hoon Han, Yoon Bin Jung, Yohan Jo, Edward Choi
| Challenge: | Clinical notes are an extensive repository of information specific to individual patients. |
| Approach: | They create synthetic large-scale clinical notes using publicly available case reports extracted from biomedical literature and train a clinical large language model, Asclepius. |
| Outcome: | The proposed model outperforms several other models and is supported by detailed evaluations conducted by GPT-4 and medical professionals. |
A Large-Scale Real-World Evaluation of an LLM-Based Virtual Teaching Assistant (2025.acl-industry)
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| Challenge: | Empirical studies on their effectiveness and acceptance in real-world classrooms are limited, leaving their practical impact uncertain. |
| Approach: | They develop an LLM-based virtual teaching assistant and deploy it in an introductory AI programming course with 477 graduate students. |
| Outcome: | The proposed system is tested in an introductory AI programming course with 477 graduate students. |
Open-WikiTable : Dataset for Open Domain Question Answering with Complex Reasoning over Table (2023.findings-acl)
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| Challenge: | Open-WikiTable is the first open domain question answering dataset that requires complex reasoning over tables. |
| Approach: | They propose to use open-domain question answering over tables to extract questions from tables. |
| Outcome: | The dataset is publicly available. it is built upon WikiSQL and WikiTableQuestions. |