Papers by Brian Kwon
MedJEx: A Medical Jargon Extraction Model with Wiki’s Hyperlink Span and Contextualized Masked Language Model Score (2022.emnlp-main)
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| Challenge: | Existing natural language processing (NLP) methods for identifying medical jargon terms are difficult for patients to understand. |
| Approach: | They propose a natural language processing application for identifying medical jargon terms from electronic health record notes. |
| Outcome: | The proposed model outperforms state-of-the-art models on an auxiliary Wikipedia hyperlink span dataset and on the annotated MedJ dataset. |
Shall We Team Up: Exploring Spontaneous Cooperation of Competing LLM Agents (2024.findings-emnlp)
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Zengqing Wu, Run Peng, Shuyuan Zheng, Qianying Liu, Xu Han, Brian Kwon, Makoto Onizuka, Shaojie Tang, Chuan Xiao
| Challenge: | Large Language Models (LLMs) are increasingly used in social simulations, where they are guided by carefully crafted instructions to exhibit human-like behaviors. |
| Approach: | They propose to use Large Language Models (LLMs) as agents to simulate the gradual transition from non-cooperative to cooperative behaviors of agents. |
| Outcome: | The proposed model can simulate the gradual transition from non-cooperative to cooperative behaviors in three competitive scenarios. |