2 citations · 2 across the 5 of their papers we have counts for
4 papers · 1 filter
Watch Before You Answer: Learning from Visually Grounded Post-Training
Yuxuan Zhang, EunJeong Hwang, Huaisong Zhang +8
It is critical for vision-language models (VLMs) to comprehensively understand visual, temporal, and textual cues. However, despite rapid progress in multimodal modeling, video und…
VideoScore2: Think before You Score in Generative Video Evaluation
Xuan He, Dongfu Jiang, Ping Nie +21
Recent advances in text-to-video generation have produced increasingly realistic and diverse content, yet evaluating such videos remains a fundamental challenge due to their multi-…
VideoEval-Pro: Robust and Realistic Long Video Understanding Evaluation
Wentao Ma, Weiming Ren, Yiming Jia +4
Large multimodal models (LMMs) have recently emerged as a powerful tool for long video understanding (LVU), prompting the development of standardized LVU benchmarks to evaluate the…
VisualWebInstruct: Scaling up Multimodal Instruction Data through Web Search
Yiming Jia, Jiachen Li, Xiang Yue +4
Vision-Language Models have made significant progress on many perception-focused tasks. However, their progress on reasoning-focused tasks remains limited due to the lack of high-q…