Information Retrieval

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Scoured 236 posts in 5.1 ms

Best practices for building a modern app with vector search

 🔍Semantic Search  Content type: Blog
elastic.co·

When More Documents Hurt RAG: Mitigating Vector Search Dilution with Domain-Scoped, Model-Agnostic Retrieval

 📚RAG  Content type: Academic
arxiv.org·

Managing Elasticsearch Reindex at Scale: Performance, Reliability, and Observability

 📚RAG  Content type: Blog
blog.palantir.com·

AI context windows: Why context quality beats context size

 🧠Context Engineering  Content type: Blog
redis.io·

On Arithmetic Private Information Retrieval: Why Code-Based PIR (Usually) Fails

 🗄️Vector Databases
eprint.iacr.org·

The Retrieval Audit: Why Your RAG Gives Confident Wrong Answers

 📚RAG  Content type: Blog
medium.com
·

TurboQuant in PostgreSQL

 🔍Semantic Search  Content type: Blog
blog.mayflower.de·

LangChain vs LlamaIndex 2026: Response Time on 10 RAG Tasks

 📚RAG  Content type: Blog  Content type: Discussion
tildalice.io·

I built an AI that screens resumes — here’s what the data actually showed

 📚RAG  Content type: Blog
medium.com
·

Hybrid Search for RAG: Fix Retrieval Accuracy in AI

 📚RAG  Content type: Blog
pingcap.com·

Explore OpenSearch 3.7

 🔍Semantic Search  Content type: Blog
opensearch.org·

The Clock Said Valid. The World Said Otherwise. *CLAIM-24 update — Self-Correcting Systems series*

 🔢Embeddings  Content type: Code
github.com··DEV

Agentic AI Architecture: How CockroachDB Supports Memory, Context, and Control

 🤖LLM Agents  Content type: Blog
cockroachlabs.com·

Show HN: Lore – LLM proxy for coding agent context and memory management

 🧠Context Engineering
withlore.ai··Hacker News

How I benchmarked a 100% local RAG pipeline to 9/9 (zero API keys)

 📚RAG
buy.polar.sh··DEV

Bridging Multi-Vector and Learned-Sparse Retrieval, A Diagnostic Framework for Robust Semantic IDs, and More!

 📚RAG  Content type: News  Content type: Blog

New comment by curiouser12 in "Ask HN: Who wants to be hired? (June 2026)"

 💬LLMs

Show HN: YourMemory, agentic memory is a pruning problem, not a hoarding problem

 🔍Semantic Search  Content type: Discussion

Your AI agent reads the fine print: building a RAG pipeline over EU regulations with Elasticsearch and OGX

 📚RAG  Content type: Blog
elastic.co·

Redis vs Memorystore: key differences in 2026

 🔍Semantic Search  Content type: Blog
redis.io·

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