Akshay (@akshay_pachaar)RAG 시스템의 검색 성능이 5천 개 문서에서는 90%였지만 50만 개 문서로 확장하자 50%로 급락하는 사례를 제시하며, 동일한 임베딩 모델과 리트리버를 써도 문서 규모 증가가 성능 저하를 유발할 수 있음을 짚는다. 대규모 RAG 설계의 핵심 문제를 묻는 LLM 인터뷰 질문이다.https://x.com/akshay_pachaar/status/2052371239520629243#rag #llm #embeddings #retrieval #nlp
Related
📰 The UK Finally Starts Reforming Its 'Computer Misuse Act'Computer Weekly reports on "the long-awaited reform of Britai...
📰 The UK Finally Starts Reforming Its 'Computer Misuse Act'Computer Weekly reports on "the long-awaited reform of Britain's outdated Computer Misuse Act of 1990 — which has hamstru...
Software Engineering Radio used to be one of my favorite podcasts.I didn't listen to even half the episodes, but kept fi...
Software Engineering Radio used to be one of my favorite podcasts.I didn't listen to even half the episodes, but kept finding ones I really enjoyed.A while ago, they stopped provid...
📰 SHAP Explainability Guide 2026: 5 Key Techniques to Interpret Black-Box ModelsA new coding guide provides a practical ...
📰 SHAP Explainability Guide 2026: 5 Key Techniques to Interpret Black-Box ModelsA new coding guide provides a practical framework for implementing SHAP explainability workflows, mo...