Visual Embodied Brain-1.5 (VeBrain-1.5) is presented, a task-level unified framework that connects multimodal perception and spatial reasoning with robot control through a shared MLLM-compatible decision interface and shows strong adaptability, flexibility, and compositional capabilities compared to existing methods.
Gan-Lin Yang, G. Luo, Ziyang Gong et al.· IEEE Transactions on Pattern...· 2 citations
This work introduces A 2 -Judger, a novel MLLM-based A gentic instantiation of A uto Judger equipped with semantic-aware retrieval and dynamic memory that significantly improves sample efficiency while maintaining reliable evaluation results.
Xuanwen Ding, Chengjun Pan, Zejun Li et al.· 0 citations
Existing scaling strategies for Multimodal Large Language Models (MLLMs) typically expand either model parameters or sequential inference computation, incurring substantial memory or latency overhead. More importantly, most existing methods fail to alter the rigid, fixed computation allocation between the Vision Transf...
Yang Yang, Qinyu Zhao, Mou-Xiang Chen et al.· 0 citations
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