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20232026
most citedVision-R1: Incentivizing Reasoning Capability in Multimodal Large Language Models

1 citations · 2 across the 13 of their papers we have counts for

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Showing 2025 · cs.CVShow all

6 papers · 2 filters

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

ReactDance: Hierarchical Representation for High-Fidelity and Coherent Long-Form Reactive Dance Generation

Jingzhong Lin, Xinru Li, Yuanyuan Qi +8

Reactive dance generation (RDG), the task of generating a dance conditioned on a lead dancer's motion, holds significant promise for enhancing human-robot interaction and immersive…

cs.CV2025

TimeSoccer: An End-to-End Multimodal Large Language Model for Soccer Commentary Generation

Ling You, Wenxuan Huang, Xinni Xie +5

Soccer is a globally popular sporting event, typically characterized by long matches and distinctive highlight moments. Recent advances in Multimodal Large Language Models (MLLMs)…

cs.CV2025

VCR-Bench: A Comprehensive Evaluation Framework for Video Chain-of-Thought Reasoning

Yukun Qi, Yiming Zhao, Yu Zeng +7

The advancement of Chain-of-Thought (CoT) reasoning has significantly enhanced the capabilities of large language models (LLMs) and large vision-language models (LVLMs). However, a…

cs.CV2025

LLaVA-RadZ: Can Multimodal Large Language Models Effectively Tackle Zero-shot Radiology Recognition?

Bangyan Li, Wenxuan Huang, Zhenkun Gao +8

Recently, Multimodal Large Language Models (MLLMs) have demonstrated exceptional capabilities in visual understanding and reasoning across various vision-language tasks. However, w…

cs.CV2025★ 1 cited

Vision-R1: Incentivizing Reasoning Capability in Multimodal Large Language Models

Wenxuan Huang, Bohan Jia, Zijie Zhai +7

DeepSeek-R1-Zero has successfully demonstrated the emergence of reasoning capabilities in LLMs purely through Reinforcement Learning (RL). Inspired by this breakthrough, we explore…