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VideoJev: System One Model for Video Understanding and Interaction
Yuhan Zhu, Xiangyu Zeng, Qingyi Si +15
Visual agents must turn video observations into timely decisions to track progress and choose what to do next. Building on the emerging System One paradigm, we introduce VideoJev,…
JoyAI-VL-Interaction: Real-Time Vision-Language Interaction Intelligence
Dingyu Yao, Junhao Zhou, Chenxu Yang +17
Many moments in the real world do not wait for a user to ask. A fire starts on a security monitor, an expression flickers across a video call, or a product a viewer wants flashes b…
Harnessing Streaming Video in the Wild
Dingyu Yao, Shuhuan Gu, Qingyi Si +8
Vision-Language Models (VLMs) are increasingly required to process unbounded video streams in applications such as video-call assistants, live commentary, and embodied robots. An i…
Find, Fix, Reason: Context Repair for Video Reasoning
Haojian Huang, Chuanyu Qin, Yinchuan Li +1
Reinforcement learning has advanced video reasoning in large multi-modal models, yet dominant pipelines either rely on on-policy self-exploration, which plateaus at the model's kno…
EasyVideoR1: Easier RL for Video Understanding
Chuanyu Qin, Chenxu Yang, Qingyi Si +6
Reinforcement learning from verifiable rewards (RLVR) has demonstrated remarkable effectiveness in improving the reasoning capabilities of large language models. As models evolve i…
Trusted Unified Feature-Neighborhood Dynamics for Multi-View Classification
Haojian Huang, Chuanyu Qin, Zhe Liu +6
Multi-view classification (MVC) faces inherent challenges due to domain gaps and inconsistencies across different views, often resulting in uncertainties during the fusion process.…