7 papers
DataEvolver: Let Your Data Build and Improve Itself via Goal-Driven Loop Agents
Qisong Zhang, Wenzhuo Wu, Zhuangzhuang Jia +7
Constructing controllable visual data is a major bottleneck for image editing and multimodal understanding. Useful supervision is rarely produced by a single rendering pass; instea…
DetailVerifyBench: A Benchmark for Dense Hallucination Localization in Long Image Captions
Xinran Wang, Yuxuan Zhang, Xiao Zhang +7
Accurately detecting and localizing hallucinations is a critical task for ensuring high reliability of image captions. In the era of Multimodal Large Language Models (MLLMs), capti…
Generative Visual Chain-of-Thought for Image Editing
Zijin Yin, Tiankai Hang, Yiji Cheng +9
Existing image editing methods struggle to perceive where to edit, especially under complex scenes and nuanced spatial instructions. To address this issue, we propose Generative Vi…
Benchmarking Semantic Segmentation Models via Appearance and Geometry Attribute Editing
Zijin Yin, Bing Li, Kongming Liang +4
Semantic segmentation takes pivotal roles in various applications such as autonomous driving and medical image analysis. When deploying segmentation models in practice, it is criti…
Hepato-LLaVA: An Expert MLLM with Sparse Topo-Pack Attention for Hepatocellular Pathology Analysis on Whole Slide Images
Yuxuan Yang, Zhonghao Yan, Yi Zhang +6
Hepatocellular Carcinoma diagnosis relies heavily on the interpretation of gigapixel Whole Slide Images. However, current computational approaches are constrained by fixed-resoluti…
Entropy-Adaptive Fine-Tuning: Resolving Confident Conflicts to Mitigate Forgetting
Muxi Diao, Lele Yang, Wuxuan Gong +6
Supervised Fine-Tuning (SFT) is the standard paradigm for domain adaptation, yet it frequently incurs the cost of catastrophic forgetting. In sharp contrast, on-policy Reinforcemen…