TE
科技回声
首页24小时热榜最新最佳问答展示工作
GitHubTwitter
首页

科技回声

基于 Next.js 构建的科技新闻平台,提供全球科技新闻和讨论内容。

GitHubTwitter

首页

首页最新最佳问答展示工作

资源链接

HackerNews API原版 HackerNewsNext.js

© 2025 科技回声. 版权所有。

Evaluating RAG for large scale codebases

41 点作者 GavCo3 个月前

3 条评论

jimminyx3 个月前
Conceptually, LLM-as-a-judge doesn't feel like it should work — it's like asking a student to grade their own homework. it's very unintuitive for me that it actually seems to work pretty well
评论 #43046366 未加载
评论 #43051458 未加载
评论 #43047443 未加载
评论 #43047676 未加载
33a3 个月前
If the self evaluation makes it better, then why not do the self evaluation as part of the normal RAG workflow?
namanyayg3 个月前
Who's data are they training on? Are they storing and using all customer data?
评论 #43047659 未加载