Records found: 7
'Pyversity is a lightweight Python library that re-ranks retrieval outputs to balance relevance and diversity. This guide shows how MMR and MSD reduce redundant results with practical code examples.'
'Hands-on tutorial: build an Agentic RAG pipeline that decides whether to retrieve, picks the right retrieval strategy, and synthesizes context-rich answers using embeddings and FAISS.'
'IBM published two ModernBERT-based Granite R2 embeddings offering 8k context, compact architectures, and high retrieval throughput suitable for production RAG and search systems.'
DeepMind demonstrates a mathematical limit on fixed-size dense embeddings that causes retrieval failures in RAG systems at scale, and the LIMIT benchmark exposes this ceiling even on small toy tasks.
'Learn how to build an AI agent that summarizes recent conversations for short-term context and stores distilled facts in a FAISS-backed vector memory for long-term recall.'
'Step-by-step guide to create a Gemini-powered PaperQA2 agent that can query, compare and cite multiple research papers with example code and best practices.'
This guide shows how to build a semantic search and question-answering system using Together AI embeddings, FAISS vector search, and LangChain, all in a modular and efficient pipeline.