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cs.CV2026
Gemini Embedding 2: A Native Multimodal Embedding Model from Gemini
Madhuri Shanbhogue, Zhe Li, Shanfeng Zhang +86
We introduce Gemini Embedding 2, a native multimodal embedding model that allows embedding video, audio, image, and text modalities in a unified representation space. We leverage t…
cs.CV2026
Taking Shortcuts for Categorical VQA Using Super Neurons
Pierre Musacchio, Jaeyi Jeong, Dahun Kim +1
Sparse Attention Vectors (SAVs) have emerged as an excellent training-free alternative to supervised finetuning or low-rank adaptation to improve the performance of Vision Language…
cs.CV2024
OmniBind: Teach to Build Unequal-Scale Modality Interaction for Omni-Bind of All
Yuanhuiyi Lyu, Xu Zheng, Dahun Kim +1
Research on multi-modal learning dominantly aligns the modalities in a unified space at training, and only a single one is taken for prediction at inference. However, for a real ma…