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cs.CV2026
Magic-MM-Embedding: Towards Visual-Token-Efficient Universal Multimodal Embedding with MLLMs
Qi Li, Yanzhe Zhao, Yongxin Zhou +4
Multimodal Large Language Models (MLLMs) have shown immense promise in universal multimodal retrieval, which aims to find relevant items of various modalities for a given query. Ho…
cs.CV2025
Unleashing the Power of Vision-Language Models for Long-Tailed Multi-Label Visual Recognition
Wei Tang, Zuo-Zheng Wang, Kun Zhang +2
Long-tailed multi-label visual recognition poses a significant challenge, as images typically contain multiple labels with highly imbalanced class distributions, leading to biased…