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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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13 papers

cs.CV2026

CLIP-Map: Structured Matrix Mapping for Parameter-Efficient CLIP Compression

Kangjie Zhang, Wenxuan Huang, Xin Zhou +9

Contrastive Language-Image Pre-training (CLIP) has achieved widely applications in various computer vision tasks, e.g., text-to-image generation, Image-Text retrieval and Image cap…

cs.LG2026

Towards Efficient Large Language Reasoning Models via Extreme-Ratio Chain-of-Thought Compression

Yuntian Tang, Bohan Jia, Wenxuan Huang +7

Chain-of-Thought (CoT) reasoning successfully enhances the reasoning capabilities of Large Language Models (LLMs), yet it incurs substantial computational overhead for inference. E…

cs.CL2025

MASA: Rethinking the Representational Bottleneck in LoRA with Multi-A Shared Adaptation

Qin Dong, Yuntian Tang, Heming Jia +7

Low-Rank Adaptation (LoRA) has emerged as a dominant method in Parameter-Efficient Fine-Tuning (PEFT) for large language models, which augments the transformer layer with one down-…

cs.CL2025

MT: Scaling MLLM-based Text Image Machine Translation via Multi-Task Reinforcement Learning

Zhaopeng Feng, Yupu Liang, Shaosheng Cao +7

Text Image Machine Translation (TIMT)-the task of translating textual content embedded in images-is critical for applications in accessibility, cross-lingual information access, an…

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…