Visually-Situated Natural Language Understanding with Contrastive Reading Model and Frozen Large Language Models (2023.emnlp-main)
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Geewook Kim, Hodong Lee, Daehee Kim, Haeji Jung, Sanghee Park, Yoonsik Kim, Sangdoo Yun, Taeho Kil, Bado Lee, Seunghyun Park
| Challenge: | Recent advances in Large Language Models (LLMs) have stimulated a surge of research aimed at extending their applications to the visual domain. |
| Approach: | They propose a novel neural architecture to enhance language-image understanding capability of LLMs by capturing intricate details that are often overlooked in existing methods. |
| Outcome: | The proposed model can achieve better comprehension of language information in visual contexts within images. |
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