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20242026
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cs.CV2026

Towards Artwork Explanation in Large-scale Vision Language Models

Kazuki Hayashi, Yusuke Sakai, Hidetaka Kamigaito +2

Large-scale Vision-Language Models (LVLMs) output text from images and instructions, demonstrating capabilities in text generation and comprehension. However, it has not been clari…

cs.CV2025

Pixel Reasoner: Incentivizing Pixel-Space Reasoning with Curiosity-Driven Reinforcement Learning

Haozhe Wang, Alex Su, Weiming Ren +2

Chain-of-thought reasoning has significantly improved the performance of Large Language Models (LLMs) across various domains. However, this reasoning process has been confined excl…

cs.CV2025

Vamba: Understanding Hour-Long Videos with Hybrid Mamba-Transformers

Weiming Ren, Wentao Ma, Huan Yang +3

State-of-the-art transformer-based large multimodal models (LMMs) struggle to handle hour-long video inputs due to the quadratic complexity of the causal self-attention operations,…

cs.CV2025

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…

cs.CV2025

OmniEdit: Building Image Editing Generalist Models Through Specialist Supervision

Cong Wei, Zheyang Xiong, Weiming Ren +3

Instruction-guided image editing methods have demonstrated significant potential by training diffusion models on automatically synthesized or manually annotated image editing pairs…

cs.CV2024

VISTA: Enhancing Long-Duration and High-Resolution Video Understanding by Video Spatiotemporal Augmentation

Weiming Ren, Huan Yang, Jie Min +2

Current large multimodal models (LMMs) face significant challenges in processing and comprehending long-duration or high-resolution videos, which is mainly due to the lack of high-…