1 citations · 2 across the 11 of their papers we have counts for
12 papers
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…
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…
Can Large Language Models Model Programs Formally?
Zhiyong Chen, Jialun Cao, Jiarong Wu +2
In the digital age, ensuring the correctness, safety, and reliability of software through formal verification is paramount, particularly as software increasingly underpins critical…
SoMe: A Realistic Benchmark for LLM-based Social Media Agents
Dizhan Xue, Jing Cui, Shengsheng Qian +2
Intelligent agents powered by large language models (LLMs) have recently demonstrated impressive capabilities and gained increasing popularity on social media platforms. While LLM…
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…
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…
From Linguistic Giants to Sensory Maestros: A Survey on Cross-Modal Reasoning with Large Language Models
Shengsheng Qian, Zuyi Zhou, Dizhan Xue +2
Cross-modal reasoning (CMR), the intricate process of synthesizing and drawing inferences across divergent sensory modalities, is increasingly recognized as a crucial capability in…
Erasing Self-Supervised Learning Backdoor by Cluster Activation Masking
Shengsheng Qian, Dizhan Xue, Yifei Wang +3
Self-Supervised Learning (SSL) is an effective paradigm for learning representations from unlabeled data, such as text, images, and videos. However, researchers have recently found…
A Survey on Interpretable Cross-modal Reasoning
Dizhan Xue, Shengsheng Qian, Zuyi Zhou +1
In recent years, cross-modal reasoning (CMR), the process of understanding and reasoning across different modalities, has emerged as a pivotal area with applications spanning from…