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cs.CV2026
DyCo-RL: Dynamic Cross-Modal Coordination for Visual Reasoning
Hangui Lin, Yan Shu, Zhengyang Liang +6
Reinforcement Learning with Verifiable Rewards (RLVR) has emerged as a leading paradigm for enhancing visual reasoning in Multimodal Large Language Models (MLLMs). However, existin…
cs.CV2026
MemLens: Benchmarking Multimodal Long-Term Memory in Large Vision-Language Models
Xiyu Ren, Zhaowei Wang, Yiming Du +11
Memory is essential for large vision-language models (LVLMs) to handle long, multimodal interactions, with two method directions providing this capability: long-context LVLMs and m…
cs.CV2025
Fleming-VL: Towards Universal Medical Visual Reasoning with Multimodal LLMs
Yan Shu, Chi Liu, Robin Chen +2
Multimodal Large Language Models (MLLMs) have demonstrated remarkable effectiveness in various general-domain scenarios, such as visual question answering and image captioning. Rec…