Aravind Srinivas· @AravSrinivas · X·· 2 天前AI 评分53
AI 导读
Perplexity 开源其上下文嵌入模型，该模型在 turbopuffer 的 context-bench 上表现最佳。引用内容显示 pplx-embed-v2-context-9b-preview 采用整篇文档视野下编码每个文本块的新训练方式，在 ConTEB 和 turbopuffer 的 context-bench 上创下 SOTA，详见 https://www.perplexity.ai/hub/blog/contextual-embedding-beyond-the-gold-passage
正文
We’re open sourcing our state-of-the-art contextual embedding models, which perform best in turbopuffer’s context-bench.
We built a new way to train contextual embedding models, which encode each chunk of a document with the whole document in view. pplx-embed-v2-context-9b-preview sets a new state of the art on ConTEB and @turbopuffer's new, privately held context-bench. https://www.perplexity.ai/hub/blog/contextual-embedding-beyond-the-gold-passage在 X 查看被引用的帖子
来源：Aravind Srinivas · x.com