JevRAG变体在RAG系统中表现优异
GPT Researcher用Jev替换嵌入后，RAG系统效果显著提升，成本不变，还能完全抛弃嵌入层。
JevRAG变体在多个测试中展现出优化潜力。在GPT Researcher的RAG管道中，Jev替换嵌入后，在28个研究任务上表现更优：相关上下文增加59%（73%对比46%），盲测报告偏好比为15:3，同时成本保持不变。JevRAG结合语义搜索在论文探索中取得成功。
Lots of JevRAG variants showing up. Interesting to say the least. You can’t really make any conclusions with these scoped tests but it raises discussions and exciting directions to find optimization in current RAG and agentic systems. I have been testing a JevRAG of my own for paper exploration. So far, I have had more success with Jev for reranking and some very interesting ways to search papers combining semantic search and Jev. More on that soon. Assaf Elovic @assaf_elovic Didn't expect this 🤯 We replaced embeddings with Jev in GPT Researcher's RAG pipeline and tested both on 28 research tasks from SimpleQA and open ended research. Jev beat embeddings on every quality measure we ran: - 59% more relevant context (73% vs 46%) - Reports preferred 15 to 3 in blind comparisons - Same cost per report GPT Researcher now runs on Jev by default, and no longer needs embeddings at all. All you need is @LangChain + @tavilyai +Jev for the perfect RAG system. Check out the repo here: github.com/assafelovic/gp… q Research: docs.gptr.dev/docs/gpt-resea… q 🔗 View Quoted Tweet 💬 2 🔄 0 ❤️ 1 👀 1380 📊 2 ⚡
