3 citations · 6 across the 21 of their papers we have counts for
23 papers
SoccerNet 2026 Challenges Results
Anthony Cioppa, Silvio Giancola, Håkan Ardö +102
The SoccerNet 2026 Challenges constitute the sixth annual edition of the SoccerNet open benchmarking effort, dedicated to advancing computer vision research in sports video underst…
Temporal Evidence Routing with Structured Visual Evidence for TimeLogicQA
Yuyang Sun, Yongliang Wu, Xingyu Zhu +8
TimeLogicQA evaluates whether video question answering systems can reason over temporal relations such as event existence, ordering, persistence, boundary conditions, and overlap.…
Adaptive Dense Evidence Refinement for Video Relational Reasoning for VRR-QA Challenge
Yuyang Sun, Yongliang Wu, Xingyu Zhu +8
VRR-QA evaluates whether video-language systems can infer spatial, temporal, viewpoint, depth, and visibility relations that are not always resolved by a single frame. We present a…
Dual-Route Top-K Retrieval with 1v1 VLM Reranking for the CoVR-R
Yuyang Sun, Yongliang Wu, Xingyu Zhu +8
We describe \emph{Dual-Route Top-K Retrieval with 1v1 VLM Reranking} for the CoVR-R challenge. The method treats composed video retrieval as two coupled problems: finding a suffici…
Stop When Reasoning Converges: Semantic-Preserving Early Exit for Reasoning Models
Dehai Min, Giovanni Vaccarino, Huiyi Chen +3
Large Reasoning Models (LRMs) achieve strong performance by generating long chains of thought (CoT), but often overthink, continuing to reason after a solution has already stabiliz…
Auto-Rubric as Reward: From Implicit Preferences to Explicit Multimodal Generative Criteria
Juanxi Tian, Fengyuan Liu, Jiaming Han +6
Aligning multimodal generative models with human preferences demands reward signals that respect the compositional, multi-dimensional structure of human judgment. Prevailing RLHF a…
GEditBench v2: A Human-Aligned Benchmark for General Image Editing
Zhangqi Jiang, Zheng Sun, Xianfang Zeng +7
Recent advances in image editing have enabled models to handle complex instructions with impressive realism. However, existing evaluation frameworks lag behind: current benchmarks…
SkillRouter: Skill Routing for LLM Agents at Scale
YanZhao Zheng, ZhenTao Zhang, Chao Ma +8
Reusable skills let LLM agents package task-specific procedures, tool affordances, and execution guidance into modular building blocks. As skill ecosystems grow to tens of thousand…
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…
CoT Vectors: Transferring and Probing the Reasoning Mechanisms of LLMs
Li Li, Ziyi Wang, Yongliang Wu +2
Chain-of-Thought (CoT) prompting has emerged as a powerful approach to enhancing the reasoning capabilities of Large Language Models (LLMs). However, existing implementations, such…
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…
On the Generalization of SFT: A Reinforcement Learning Perspective with Reward Rectification
Yongliang Wu, Yizhou Zhou, Zhou Ziheng +7
In this work, we present a simple yet theoretically motivated improvement to Supervised Fine-Tuning (SFT) for the Large Language Model (LLM), addressing its limited generalization…
Unveiling Effective In-Context Configurations for Image Captioning: An External & Internal Analysis
Li Li, Yongliang Wu, Jingze Zhu +3
The evolution of large models has witnessed the emergence of In-Context Learning (ICL) capabilities. In Natural Language Processing (NLP), numerous studies have demonstrated the ef…
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…
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…
KRIS-Bench: Benchmarking Next-Level Intelligent Image Editing Models
Yongliang Wu, Zonghui Li, Xinting Hu +7
Recent advances in multi-modal generative models have enabled significant progress in instruction-based image editing. However, while these models produce visually plausible output…
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…
Video Repurposing from User Generated Content: A Large-scale Dataset and Benchmark
Yongliang Wu, Wenbo Zhu, Jiawang Cao +8
The demand for producing short-form videos for sharing on social media platforms has experienced significant growth in recent times. Despite notable advancements in the fields of v…
Number it: Temporal Grounding Videos like Flipping Manga
Yongliang Wu, Xinting Hu, Yuyang Sun +5
Video Large Language Models (Vid-LLMs) have made remarkable advancements in comprehending video content for QA dialogue. However, they struggle to extend this visual understanding…
On the Limitations and Prospects of Machine Unlearning for Generative AI
Shiji Zhou, Lianzhe Wang, Jiangnan Ye +2
Generative AI (GenAI), which aims to synthesize realistic and diverse data samples from latent variables or other data modalities, has achieved remarkable results in various domain…
Zero-Shot Long-Form Video Understanding through Screenplay
Yongliang Wu, Bozheng Li, Jiawang Cao +8
The Long-form Video Question-Answering task requires the comprehension and analysis of extended video content to respond accurately to questions by utilizing both temporal and cont…
Unlearning Concepts in Diffusion Model via Concept Domain Correction and Concept Preserving Gradient
Yongliang Wu, Shiji Zhou, Mingzhuo Yang +6
Text-to-image diffusion models have achieved remarkable success in generating photorealistic images. However, the inclusion of sensitive information during pre-training poses signi…
Reframe Anything: LLM Agent for Open World Video Reframing
Jiawang Cao, Yongliang Wu, Weiheng Chi +3
The proliferation of mobile devices and social media has revolutionized content dissemination, with short-form video becoming increasingly prevalent. This shift has introduced the…