Papers by Seeun Lee
Distilling Cross-Modal Knowledge into Domain-Specific Retrievers for Enhanced Industrial Document Understanding (2025.emnlp-industry)
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Jinhyeong Lim, Jeongwan Shin, Seeun Lee, Seongdeok Kim, Joungsu Choi, Jongbae Kim, Chun Hwan Jung, Youjin Kang
| Challenge: | Retrieval-Augmented Generation (RAG) has shown strong performance in open-domain tasks, but its effectiveness in industrial domains is limited by a lack of domain understanding and document structural elements (DSE) such as tables, figures, charts, and formula. |
| Approach: | They propose a knowledge distillation framework that transfers complementary knowledge from Large Language Models and Vision-Language Models into a compact domain-specific retriever. |
| Outcome: | The proposed framework outperforms larger baselines while requiring significantly less computational complexity. |