1 citations · 2 across the 3 of their papers we have counts for
3 papers
cs.CV2026
MTA-Agent: An Open Recipe for Multimodal Deep Search Agents
Xiangyu Peng, Can Qin, An Yan +4
Multimodal large language models (MLLMs) have demonstrated strong capabilities in visual understanding, yet they remain limited in complex, multi-step reasoning that requires deep…
cs.CV2024★ 1 cited
STLLaVA-Med: Self-Training Large Language and Vision Assistant for Medical Question-Answering
Guohao Sun, Can Qin, Huazhu Fu +2
Large Vision-Language Models (LVLMs) have shown significant potential in assisting medical diagnosis by leveraging extensive biomedical datasets. However, the advancement of medica…
cs.CV2024★ 1 cited
SQ-LLaVA: Self-Questioning for Large Vision-Language Assistant
Guohao Sun, Can Qin, Jiamian Wang +3
Recent advances in vision-language models have shown notable generalization in broad tasks through visual instruction tuning. However, bridging the gap between the pre-trained visi…