activity
20242026
collaborators

7 papers

eess.SP2026

BFLA: Block-Filtered Long-Context Attention Mechanism

Chong Wu, Zhenan Feng, Renjie Xu +5

This paper proposes Block-Filtered Long-Context Attention (BFLA), a training-free sparse prefill attention mechanism for long-context inference. BFLA adopts a two-stage design. In…

cs.AI2025

LayerCake: Token-Aware Contrastive Decoding within Large Language Model Layers

Jingze Zhu, Yongliang Wu, Wenbo Zhu +7

Large language models (LLMs) excel at natural language understanding and generation but remain vulnerable to factual errors, limiting their reliability in knowledge-intensive tasks…

cs.CV2025

OpusAnimation: Code-Based Dynamic Chart Generation

Bozheng Li, Miao Yang, Zhenhan Chen +9

Dynamic Chart Generation (DCG) involves producing code-rendered animated visualizations as charts. While recent advances in multi-modal large language models (MLLMs) have significa…

cs.CV2025

SoccerNet 2025 Challenges Results

Silvio Giancola, Anthony Cioppa, Marc Gutiérrez-Pérez +115

The SoccerNet 2025 Challenges mark the fifth annual edition of the SoccerNet open benchmarking effort, dedicated to advancing computer vision research in football video understandi…

cs.CV2025

RSVP: Reasoning Segmentation via Visual Prompting and Multi-modal Chain-of-Thought

Yi Lu, Jiawang Cao, Yongliang Wu +6

Multi-modal Large Language Models (MLLMs) have demonstrated remarkable reasoning capability while lack explicit mechanisms for visual grounding and segmentation, creating a gap bet…

cs.CV2025

VEU-Bench: Towards Comprehensive Understanding of Video Editing

Bozheng Li, Yongliang Wu, Yi Lu +7

Widely shared videos on the internet are often edited. Recently, although Video Large Language Models (Vid-LLMs) have made great progress in general video understanding tasks, thei…