Papers by Kihun Kim
ixi-GEN: Efficient Industrial sLLMs through Domain Adaptive Continual Pretraining (2025.emnlp-industry)
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Seonwu Kim, Yohan Na, Kihun Kim, Hanhee Cho, Geun Lim, Mintae Kim, Seongik Park, Ki Hyun Kim, Youngsub Han, Byoung-Ki Jeon
| Challenge: | Domain Adaptive Continual Pretraining (DACP) is a method to mitigate performance degradation in small LLMs and enhance their effectiveness in target domains. |
| Approach: | They propose a continual pretraining methodology that optimizes sLLMs within service domains and enhances their effectiveness in target domains. |
| Outcome: | The proposed model achieves significant gains in target-domain performance while preserving general capabilities, offering a cost-efficient and scalable solution for enterprise-level deployment. |
Taxonomy of Comprehensive Safety for Clinical Agents (2025.emnlp-industry)
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| Challenge: | Existing methods for ensuring safety in clinical chatbot applications are not suitable for clinical applications. |
| Approach: | They propose a fine-grained taxonomy that integrates safety filtering and tool selection into a single user intent classification step. |
| Outcome: | The proposed taxonomy integrates safety filtering and tool selection into a single user intent classification step. |
Evaluating the Pre-Consultation Ability of LLMs using Diagnostic Guidelines (2026.eacl-industry)
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Jean Seo, Gibaeg Kim, Kihun Shin, Seungseop Lim, Hyunkyung Lee, Wooseok Han, Jongwon Lee, Eunho Yang
| Challenge: | EPAG is a benchmark dataset and evaluation pipeline for pre-consultation of large language models. |
| Approach: | They propose a benchmark dataset and framework for evaluating pre-consultation ability of LLMs using diagnostic guidelines. |
| Outcome: | The proposed framework outperforms frontier LLMs in pre-consultation. |