arXiv AI
Jul 7

VideoSearcher: Empowering Video Deep Research with Multi-Tool Agentic Reasoning via Reinforcement Learning

arXiv:2607. 02927v1 Announce Type: cross Abstract: Video understanding is moving beyond closed-context perception toward open-world evidence exploration, a paradigm formalized as Video Deep Research (VDR).

By Zhenkun Gao, Yicheng Bao, Jinlong Peng, Xueheng Li, Theo Huang, Bangwei Liu, Kunquan Li, Zhenye Gan, Tao Hu, Chengjun Xie, Mingqian Yang, Xuanhua He, Zhizhong Zhang, Xin Tan, Chengjie Wang, Yuan Xie
arXiv AI
2d ago

ModalSearcher: Weaving Visual Evidence into Autonomous Cross-Modal Deep Search

ModalSearcher introduces an autonomous cross‑modal search framework that lets an agent dynamically choose among direct reasoning, text‑to‑text search, text‑to‑image search, and reverse‑image search, actively incorporating visual evidence as needed. The system builds an interleaved multimodal knowledge graph via a scalable pipeline that samples diverse paths and uses backward question construction to prevent shortcut reasoning. Trained with supervised fine‑tuning and reinforcement learning, ModalSearcher‑8B outperforms Qwen3‑VL‑8B by 16.2 accuracy points across five multimodal knowledge‑intensive QA benchmarks and shows consistent gains on active visual‑search tasks.

By Zhihan Yin, Ruyi Li, Chengyu Fang, Yifeng Yao, Nonghai Zhang, Pengfei Xiong, Terry Zhang, Huishuai Zhang, Dongyan Zhao
arXiv AI
Jun 8

MemDreamer: Decoupling Perception and Reasoning for Long Video Understanding via Hierarchical Graph Memory and Agentic Retrieval Mechanism

arXiv:2606. 07512v1 Announce Type: cross Abstract: Current Vision-Language Models struggle with hours-long videos because processing full-length visual sequences induces prohibitive token explosion and attention dilution.

By Cong Chen, Guo Gan, Kaixiang Ji, ChaoYang Zhang, Zhen Yang, Guangming Yao, Hao Chen, Jingdong Chen, Yi Yuan, Chunhua Shen