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cs.CV2026

Vision-DeepResearch: Incentivizing DeepResearch Capability in Multimodal Large Language Models

Wenxuan Huang, Yu Zeng, Qiuchen Wang +14

Multimodal large language models (MLLMs) have achieved remarkable success across a broad range of vision tasks. However, constrained by the capacity of their internal world knowled…

cs.CV2025

Actial: Activate Spatial Reasoning Ability of Multimodal Large Language Models

Xiaoyu Zhan, Wenxuan Huang, Hao Sun +11

Recent advances in Multimodal Large Language Models (MLLMs) have significantly improved 2D visual understanding, prompting interest in their application to complex 3D reasoning tas…

cs.CV2025

Interleaving Reasoning for Better Text-to-Image Generation

Wenxuan Huang, Shuang Chen, Zheyong Xie +15

Unified multimodal understanding and generation models recently have achieve significant improvement in image generation capability, yet a large gap remains in instruction followin…

cs.CV2025

CompBench: Benchmarking Complex Instruction-guided Image Editing

Bohan Jia, Wenxuan Huang, Yuntian Tang +14

While real-world applications increasingly demand intricate scene manipulation, existing instruction-guided image editing benchmarks often oversimplify task complexity and lack com…

cs.CV2025

IDMR: Towards Instance-Driven Precise Visual Correspondence in Multimodal Retrieval

Bangwei Liu, Yicheng Bao, Shaohui Lin +5

Multimodal retrieval systems are becoming increasingly vital for cutting-edge AI technologies, such as embodied AI and AI-driven digital content industries. However, current multim…