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cs.CV2026

Thinking in Video: Can Video Generators Really Reason About the Real World?

Yongheng Zhang, Guang Yang, Ruihan Hou +12

Recent advances in world models and video generation have given rise to an emerging reasoning paradigm that leverages video generative models to simulate, predict, and reason about…

cs.CV2026

OMIBench: Benchmarking Olympiad-Level Multi-Image Reasoning in Large Vision-Language Model

Qiguang Chen, Chengyu Luan, Jiajun Wu +7

Large vision-language models (LVLMs) have made substantial advances in reasoning tasks at the Olympiad level. Nevertheless, current Olympiad-level multimodal reasoning benchmarks f…

cs.CV2026

Let's Think with Images Efficiently! An Interleaved-Modal Chain-of-Thought Reasoning Framework with Dynamic and Precise Visual Thoughts

Xu Liu, Yongheng Zhang, Qiguang Chen +3

Recently, Interleaved-modal Chain-of-Thought (ICoT) reasoning has achieved remarkable success by leveraging both multimodal inputs and outputs, attracting increasing attention. Whi…

cs.CV2025

Visual Thoughts: A Unified Perspective of Understanding Multimodal Chain-of-Thought

Zihui Cheng, Qiguang Chen, Xiao Xu +8

Large Vision-Language Models (LVLMs) have achieved significant success in multimodal tasks, with multimodal chain-of-thought (MCoT) further enhancing performance and interpretabili…

cs.CV2025

MMLongCite: A Benchmark for Evaluating Fidelity of Long-Context Vision-Language Models

Keyan Zhou, Zecheng Tang, Lingfeng Ming +8

The rapid advancement of large vision language models (LVLMs) has led to a significant expansion of their context windows. However, an extended context window does not guarantee th…

cs.CV2025

Synergistic Dual Spatial-aware Generation of Image-to-Text and Text-to-Image

Yu Zhao, Hao Fei, Xiangtai Li +6

In the visual spatial understanding (VSU) area, spatial image-to-text (SI2T) and spatial text-to-image (ST2I) are two fundamental tasks that appear in dual form. Existing methods f…