Papers by Gyu-Hwung Cho
SLM as Guardian: Pioneering AI Safety with Small Language Model (2024.emnlp-industry)
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Ohjoon Kwon, Donghyeon Jeon, Nayoung Choi, Gyu-Hwung Cho, Hwiyeol Jo, Changbong Kim, Hyunwoo Lee, Inho Kang, Sun Kim, Taiwoo Park
| Challenge: | Prior safety research on large language models focused on aligning them to safety requirements, but internalizing such safeguard features into larger models brought challenges of higher training cost and unintended degradation of helpfulness. |
| Approach: | They propose a multi-task learning mechanism that integrates harmful query detection and safeguard response into a single model. |
| Outcome: | The proposed approach outperforms the publicly available LLMs in harmful query detection and safeguard response generation. |
RRADistill: Distilling LLMs’ Passage Ranking Ability for Long-Tail Queries Document Re-Ranking on a Search Engine (2024.emnlp-industry)
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Nayoung Choi, Youngjune Lee, Gyu-Hwung Cho, Haeyu Jeong, Jungmin Kong, Saehun Kim, Keunchan Park, Sarah Cho, Inchang Jeong, Gyohee Nam, Sunghoon Han, Wonil Yang, Jaeho Choi
| Challenge: | Large Language Models excel at understanding the semantic relationships between queries and documents, even with lengthy and complex long-tail queries. |
| Approach: | They propose an efficient label generation pipeline and novel sLLM training methods for both encoder and decoder models. |
| Outcome: | The proposed method improves re-ranking for long-tail queries on a Korean-based search platform. |