7 citations · 7 across the 1 of their papers we have counts for
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Detecting and Evaluating Medical Hallucinations in Large Vision Language Models
Jiawei Chen, Dingkang Yang, Tong Wu +7
Large Vision Language Models (LVLMs) are increasingly integral to healthcare applications, including medical visual question answering and imaging report generation. While these mo…
BloomScene: Lightweight Structured 3D Gaussian Splatting for Crossmodal Scene Generation
Xiaolu Hou, Mingcheng Li, Dingkang Yang +7
With the widespread use of virtual reality applications, 3D scene generation has become a new challenging research frontier. 3D scenes have highly complex structures and need to en…
MCCD: Multi-Agent Collaboration-based Compositional Diffusion for Complex Text-to-Image Generation
Mingcheng Li, Xiaolu Hou, Ziyang Liu +7
Diffusion models have shown excellent performance in text-to-image generation. Nevertheless, existing methods often suffer from performance bottlenecks when handling complex prompt…
CoMT: Chain-of-Medical-Thought Reduces Hallucination in Medical Report Generation
Yue Jiang, Jiawei Chen, Dingkang Yang +5
Automatic medical report generation (MRG), which possesses significant research value as it can aid radiologists in clinical diagnosis and report composition, has garnered increasi…
Large Vision-Language Models as Emotion Recognizers in Context Awareness
Yuxuan Lei, Dingkang Yang, Zhaoyu Chen +3
Context-aware emotion recognition (CAER) is a complex and significant task that requires perceiving emotions from various contextual cues. Previous approaches primarily focus on de…
Can LLMs' Tuning Methods Work in Medical Multimodal Domain?
Jiawei Chen, Yue Jiang, Dingkang Yang +4
While Large Language Models (LLMs) excel in world knowledge understanding, adapting them to specific subfields requires precise adjustments. Due to the model's vast scale, traditio…