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cs.CV2026
Divide-and-Conquer Inference for Large-Scale Visual Recognition with Multimodal Large Language Models
Zhipeng Ye, Jiaqi Huang, Feng Jiang +5
Multimodal Large Language Models (MLLMs) have demonstrated strong capabilities across a wide range of vision language tasks. However, when applied to large scale image classificati…
cs.CV2026
AoE: Always-on Egocentric Human Video Collection for Embodied AI
Bowen Yang, Zishuo Li, Yang Sun +15
Embodied foundation models require large-scale, high-quality real-world interaction data for pre-training and scaling. However, existing data collection methods suffer from high in…