2 citations · 2 across the 7 of their papers we have counts for
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An Interpretable Local Editing Model for Counterfactual Medical Image Generation
Hyungi Min, Taeseung You, Hangyeul Lee +2
Counterfactual medical image generation have emerged as a critical tool for enhancing AI-driven systems in medical domain by answering "what-if" questions. However, existing approa…
Do You Keep an Eye on What I Ask? Mitigating Multimodal Hallucination via Attention-Guided Ensemble Decoding
Yeongjae Cho, Keonwoo Kim, Taebaek Hwang +1
Recent advancements in Large Vision-Language Models (LVLMs) have significantly expanded their utility in tasks like image captioning and visual question answering. However, they st…
CL3DOR: Contrastive Learning for 3D Large Multimodal Models via Odds Ratio on High-Resolution Point Clouds
Keonwoo Kim, Yeongjae Cho, Taebaek Hwang +2
Recent research has demonstrated that Large Language Models (LLMs) are not limited to text-only tasks but can also function as multimodal models across various modalities, includin…
Pretraining Vision-Language Model for Difference Visual Question Answering in Longitudinal Chest X-rays
Yeongjae Cho, Taehee Kim, Heejun Shin +2
Difference visual question answering (diff-VQA) is a challenging task that requires answering complex questions based on differences between a pair of images. This task is particul…