Papers by SeungWoo Shin
X-LLaVA: Optimizing Bilingual Large Vision-Language Alignment (2024.findings-naacl)
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DongJae Shin, HyeonSeok Lim, Inho Won, ChangSu Choi, Minjun Kim, SeungWoo Song, HanGyeol Yoo, SangMin Kim, KyungTae Lim
| Challenge: | constructing multilingual data for large multimodal models presents its own set of challenges due to language diversity and complexity. |
| Approach: | They propose to use GPT4-V to construct multimodal training datasets using a text-only version of GPT4. |
| Outcome: | The proposed method performs well in Korean and English, surpassing existing methods. |
Being Kind Isn’t Always Being Safe: Diagnosing Affective Hallucination in LLMs (2026.findings-eacl)
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| Challenge: | Large language models (LLMs) are increasingly engaged in emotionally vulnerable conversations that extend beyond information seeking to moments of personal distress. |
| Approach: | They propose AHaBench, a benchmark of 500 mental-health-related prompts with expert-informed reference responses, evaluated along three dimensions: Emotional Enmeshment, Illusion of Presence, and Fostering Overdependence. |
| Outcome: | The proposed model is based on 500 mental-health-related prompts with expert-informed reference responses and a 5K-instance preference dataset enabling direct preference optimization (DPO) for alignment with emotionally responsible behavior. |