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VideoResearcher: Self-Improving Tool Design for Long-Video Understanding
Dingqiang Ye, Dongdi Zhao, Kaishen Wang +11
Video agents have made substantial progress in long-video understanding. Yet effective video-agent systems require costly, time-consuming manual design and trial and error. Current…
Where to Look Matters: On-Policy Self-Distillation for Long-Video Understanding
Kaishen Wang, Dongdi Zhao, Yijun Liang +4
Vision-language models (VLMs) have made substantial progress in long-video understanding, with standard backbone models typically answering questions from frames sampled across the…
Self-Supervised Visual On-Policy Distillation
Yijiang Li, Yijun Liang, Yunjie Tian +6
Visual on-policy distillation relies heavily on an informative teacher-student asymmetry, through either a larger, stronger teacher or privileged supervision, such as reference ans…
Visual Contrastive Self-Distillation
Yijun Liang, Yunjie Tian, Yijiang Li +5
On-policy self-distillation (OPSD) removes the external teacher required by on-policy distillation (OPD), but still needs asymmetric information between teacher and student so that…
Self-Evolving Visual Questioner
Yijun Liang, Hengguang Zhou, Ming Li +3
Vision-language models (VLMs) are typically trained as passive answerers, while their ability to actively ask diverse, non-trivial, visual-centric and grounded questions remains un…
V-REX: Benchmarking Exploratory Visual Reasoning via Chain-of-Questions
Chenrui Fan, Yijun Liang, Shweta Bhardwaj +3
While many vision-language models (VLMs) are developed to answer well-defined, straightforward questions with highly specified targets, as in most benchmarks, they often struggle i…
CaughtCheating: Is Your MLLM a Good Cheating Detective? Exploring the Boundary of Visual Perception and Reasoning
Ming Li, Chenguang Wang, Yijun Liang +6
Recent agentic Multi-Modal Large Language Models (MLLMs) such as GPT-o3 have achieved near-ceiling scores on various existing benchmarks, motivating a demand for more challenging t…
ColorBench: Can VLMs See and Understand the Colorful World? A Comprehensive Benchmark for Color Perception, Reasoning, and Robustness
Yijun Liang, Ming Li, Chenrui Fan +7
Color plays an important role in human perception and usually provides critical clues in visual reasoning. However, it is unclear whether and how vision-language models (VLMs) can…
Diffusion Curriculum: Synthetic-to-Real Data Curriculum via Image-Guided Diffusion
Yijun Liang, Shweta Bhardwaj, Tianyi Zhou
Low-quality or scarce data has posed significant challenges for training deep neural networks in practice. While classical data augmentation cannot contribute very different new da…