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About this paper
Henrique Schechter Vera, Sahil Dua, Jovan Andonov, Sara Smoot, Sebastian Russo, Ivan Llanos, Max Matveev, Jae Hyeon Yoo and 65 more
EmbeddingGemma 2 maps text, images, audio, and video into an embedding space for retrieval. Modality encoders turn media into tokens that a transformer pools into a vector; modular configurations omit encoders not needed. On MSEB(Retrieval), native audio scores 69.54 MRR@10 versus 57.59 for ASR/text, but uses more parameters. An intermediate MMEB-v2 ablation improves image and video scores, while visual-document performance remains nearly unchanged.
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