Unverified50% confidenceFactExact time
EmbeddingGemma 2 supports arbitrary cross-modal retrieval among four modalities, enabling text-to-image, image-to-video, and video-to-audio searches
1
Sources
50%
Confidence
Long-term
Relevance
10/8/2026
First Seen
Sources
Related Entities
Related Claims
Partially VerifiedIn addition to text and images, EmbeddingGemma2 also supports audio and video, converting content of different modalities into 768-dimensional vectors.75% similarUnverifiedEmbeddingGemma 2 is capable of handling multiple types of tasks within the same model, including text, code, images, video, and audio.73% similarUnverifiedEmbeddingGemma 2 is the first to unify text, code, images, video, and audio into a single embedding space, and is optimized for edge deployment to support local RAG.71% similarVerifiedCurrent mainstream multimodal LLMs convert images into token sequences via a visual encoder (typically CLIP or ViT series) and then align them with the text space through a linear projection layer or cross-attention mechanism.68% similarUnverified图像条件化方案通常借助CLIP视觉编码器（ViT架构）将参考图映射到与文本嵌入共享的语义空间，再通过交叉注意力（Cross-Attention）机制将视觉特征注入UNet的去噪过程68% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/989089API
curl https://kongchang.com/api/v1/knowledge/claims/989089MCP
get_claim(id=989089)