3 citations · 4 across the 10 of their papers we have counts for
11 papers
Moment-Video: Diagnosing Temporal Fidelity of Video MLLMs on Momentary Visual Events
Xiaolin Liu, Yilun Zhu, Xiangyu Zhao +9
Video multimodal large language models (MLLMs) have made rapid progress in general and long-form video understanding, yet their ability to capture and use brief, answer-critical vi…
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…
When Parallelism Pays Off: Cohesion-Aware Task Partitioning for Multi-Agent Coding
Xu Yang, Lunyiu Nie, Ethan Chandra +3
Multi-agent Large Language Model (LLM) systems offer a way to decompose complex tasks, such as coding, through parallelization and context isolation. However, adding agents in prac…
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…
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…
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…
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…