Multi-turn visual search agents answer questions about high-resolution images by iteratively deciding where to look. Reinforcement learning for these agents rewards only the final answer, leaving the search process unsupervised. Consequently, faulty routes in which the reasoning process is erroneous yet the final resul...
Zhangquan Chen, Yao-Xin Niu, Xiang An et al.· 0 citations
Spatial-OPSD, a label-free self-improvement framework that instead exploits spatial structure naturally available from perception and reconstruction tools, is introduced, achieving the highest average among the open models and the best results on three of five spatial reasoning benchmarks.
Zhen-Yu Liu, Zhangquan Chen, Ke-Yi Chen et al.· 0 citations
EviViT, a lightweight attachment that learns where a pretrained vision transformer should acquire detail, is introduced, a lightweight attachment that learns where a pretrained vision transformer should acquire detail without refitting.
Yao-Xin Niu, Zhangquan Chen, Yang Zhang et al.· 0 citations
A memory-free recent-window protocol is fixed and a transparent and reproducible reference for open-source streaming-video research is provided, combining verifiable streaming-video data, thinking-mode OPD, and instruct-mode deployment.
Keming Wu, Baoyi Wang, Kai-Chen Zhang et al.· 0 citations
This paper proposes a simple but efficient MLLM-based framework StreamingRVOS, which can extend image-level segmentation to video-level via a streaming pipeline without introducing extra parameters and achieves excellent performance in referring video segmentation.
Wenkang Zhang, Kaicheng Yang, Xiang An et al.· 0 citations
Mage-VL is presented, an efficient codec-native streaming foundation model for real-time multimodal understanding and interaction and establishes AI4AI data pipelines encompassing prompt-code joint optimization for multimodal captioning and AI-driven performance diagnosis to guide training recipes.
