2 citations · 4 across the 12 of their papers we have counts for
11 papers · 1 filter
VideoEvoHarness: Self Evolving Agent Harness from Unlabeled Videos for Video Understanding
Weixin Xu, Yifan Liu, Yi Wang +5
Video understanding agents rely on a harness to acquire evidence, use tools, and reason, but improving it requires substantial effort. Recent self evolution methods seek to optimiz…
VideoScout: Learning Agentic Active Exploration with Adaptive Reasoning Pacing for Long Video Understanding
Weixin Xu, Zhenyu Yang, Bing Wang +2
Multimodal Large Language Models (MLLMs) have achieved remarkable progress on short video understanding yet remain limited on long videos due to the limited visual context window.…
Annotations as Rollouts: Efficient and Scalable Reinforcement Learning for Video MLLMs
Yunheng Li, Guohong Mu, Hao Li +4
Multimodal large language models (MLLMs) have become a prevailing paradigm for unified video perception. However, post-training on large multi-task datasets remains challenging, as…
ViQ: Text-Aligned Visual Quantized Representations at Any Resolution
Xumin Yu, Zuyan Liu, Zhenyu Yang +5
A unified representation for text and vision is a natural pursuit, as it enables simpler multimodal modeling and more efficient training. However, representing images as discrete s…
LiveStarPro: Proactive Streaming Video Understanding with Hierarchical Memory for Long-Horizon Streams
Zhenyu Yang, Kairui Zhang, Bing Wang +2
Despite the remarkable progress of Video Large Language Models (Video-LLMs), current online architectures still struggle to simultaneously process continuous video streams, decide…
Never Seen Before: Benchmarking Genuine Zero-Shot Composed Image Retrieval with Consistent Video-Sourced Datasets
Zhenyu Yang, Zemin Du, Shengsheng Qian +1
Zero-Shot Composed Image Retrieval (ZS-CIR) aims to retrieve a target image based on a query composed of a reference image and a relative caption without training samples. Existing…
Don't Pause: Streaming Video-Language Synchrony for Online Video Understanding
Zhenyu Yang, Kairui Zhang, Shengsheng Qian +2
Online Video Large Language Models (Video-LLMs) have advanced toward seamless human-AI interaction through frame-by-frame processing and proactive responding. However, a critical c…
LiveStar: Live Streaming Assistant for Real-World Online Video Understanding
Zhenyu Yang, Kairui Zhang, Yuhang Hu +7
Despite significant progress in Video Large Language Models (Video-LLMs) for offline video understanding, existing online Video-LLMs typically struggle to simultaneously process co…
StreamingCoT: A Dataset for Temporal Dynamics and Multimodal Chain-of-Thought Reasoning in Streaming VideoQA
Yuhang Hu, Zhenyu Yang, Shihan Wang +5
The rapid growth of streaming video applications demands multimodal models with enhanced capabilities for temporal dynamics understanding and complex reasoning. However, current Vi…
Short-video Propagation Influence Rating: A New Real-world Dataset and A New Large Graph Model
Dizhan Xue, Shengsheng Qian, Chuanrui Hu +1
Short-video platforms have gained immense popularity, captivating the interest of millions, if not billions, of users globally. Recently, researchers have highlighted the significa…
SVBench: A Benchmark with Temporal Multi-Turn Dialogues for Streaming Video Understanding
Zhenyu Yang, Yuhang Hu, Zemin Du +6
Despite the significant advancements of Large Vision-Language Models (LVLMs) on established benchmarks, there remains a notable gap in suitable evaluation regarding their applicabi…