9 citations · 14 across the 21 of their papers we have counts for
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cs.CV2026
Ground What You See: Hallucination-Resistant MLLMs via Caption Feedback, Diversity-Aware Sampling, and Conflict Regularization
Miao Pan, Wangjie Gan, Jintao Chen +4
While Multimodal Large Language Models (MLLMs) have achieved remarkable success across diverse tasks, their practical deployment is severely hindered by hallucination issues, which…
cs.CV2026★ 1 cited
IBISAgent: Reinforcing Pixel-Level Visual Reasoning in MLLMs for Universal Biomedical Object Referring and Segmentation
Yankai Jiang, Qiaoru Li, Binlu Xu +6
Recent research on medical MLLMs has gradually shifted its focus from image-level understanding to fine-grained, pixel-level comprehension. Although segmentation serves as the foun…
cs.CV2025
TK-Mamba: Marrying KAN With Mamba for Text-Driven 3D Medical Image Segmentation
Haoyu Yang, Yutong Guan, Meixing Shi +8
3D medical image segmentation is important for clinical diagnosis and treatment but faces challenges from high-dimensional data and complex spatial dependencies. Traditional single…