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20242026
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cs.CV2026

ConfusionBench: An Expert-Validated Benchmark for Confusion Recognition and Localization in Educational Videos

Lu Dong, Xiao Wang, Mark Frank +3

Recognizing and localizing student confusion from video is an important yet challenging problem in educational AI. Existing confusion datasets suffer from noisy labels, coarse temp…

cs.CV2026

UniFlow: A Unified Pixel Flow Tokenizer for Visual Understanding and Generation

Zhengrong Yue, Haiyu Zhang, Xiangyu Zeng +7

Tokenizer is a crucial component for both visual understanding and generation. To advance toward the ultimate goal of universal modeling, recent research has focused on developing…

cs.CV2025

VideoChat-R1: Enhancing Spatio-Temporal Perception via Reinforcement Fine-Tuning

Xinhao Li, Ziang Yan, Desen Meng +7

Reinforcement Learning (RL) benefits Large Language Models (LLMs) for complex reasoning. Inspired by this, we explore integrating spatio-temporal specific rewards into Multimodal L…

cs.CV2025

VideoTG-R1: Boosting Video Temporal Grounding via Curriculum Reinforcement Learning on Reflected Boundary Annotations

Lu Dong, Haiyu Zhang, Han Lin +8

Video temporal grounding (VTG) aims to locate precise segments in videos based on language queries, which is a fundamental challenge in video understanding. While recent Multimodal…

cs.CV2025

LvBench: A Benchmark for Long-form Video Understanding with Versatile Multi-modal Question Answering

Hongjie Zhang, Lu Dong, Yi Liu +4

Despite remarkable recent progress, existing long-form VideoQA datasets fall short of meeting the criteria for genuine long-form video understanding. This is primarily due to the u…

cs.CV2025

Weakly Supervised Temporal Sentence Grounding via Positive Sample Mining

Lu Dong, Haiyu Zhang, Hongjie Zhang +5

The task of weakly supervised temporal sentence grounding (WSTSG) aims to detect temporal intervals corresponding to a language description from untrimmed videos with only video-le…