Unverified60% confidenceFactTime unknown
Modern Embedding models (such as OpenAI's text-embedding-ada-002 and Alibaba's Qianwen Embedding series) can encode entire sentences or paragraphs into fixed-dimension dense vectors, typically 768 or 1024 dimensions.
2
Sources
60%
Confidence
Long-term
Relevance
6/1/2026
First Seen
Sources
Related Entities
Related Claims
Unverified嵌入模型可将文本压缩为1536维或1024维的浮点向量，OpenAI的text-embedding-ada-002和Cohere的embed-multilingual是常见示例80% similarUnverifiedRAG的向量检索依赖Embedding模型将文本编码为稠密向量，通常为512至4096维，通过余弦相似度或内积计算语义距离74% similarVerifiedText is encoded by an Embedding model into floating-point vectors of 768 to 3072 dimensions, stored in a vector database, and similarity retrieval is completed at millisecond speed via approximate nearest neighbor algorithms (HNSW, IVF, etc.).74% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/26805API
curl https://kongchang.com/api/v1/knowledge/claims/26805MCP
get_claim(id=26805)