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

 🔍Information Retrieval  Content type: Academic
arxiv.org·
Less-relevant results

Deep Dive into LLM Token Cost — Blog Series Part 2: How Prompt Caching Actually Works

 🧩Cognitive Science  Content type: Blog

Sales Is the Customer Clock

 🧠LLMs
hari.computer··Hacker News

Agentic Search Models with OpenSearch and Elasticsearch

 🔍Information Retrieval  Content type: Blog
bonsai.io··Hacker News

The Wrong Epsilon to the Brain

 🧠LLMs

Show HN: The Deterministic Core Architecture for AI-Augmented Applications

 🎮Reinforcement Learning

NightFeats @ MMU-RAGent NeurIPS 2025: A Context-Optimized Multi-Agent RAG System for the Text-to-Text Track

 🧠LLMs  Content type: Academic
arxiv.org·

An interactive introduction to the terrific experience of rendering Arabic and its technical debt

 🧠LLMs  Content type: Blog

GitLab: Built for the agentic engineering era

 📞Function Calling  Content type: Blog

uva-irlab-conv at SemEval-2026 Task 8: Multi-Turn RAG with Learned Sparse Retrieval and Listwise Reranking

 🧠LLMs  Content type: Academic
arxiv.org·

manavgup/context-analyzer: Context window usage analyzer for Claude Code — MCP server + interactive dashboard

 🐍Python  Content type: Code
github.com··Hacker News

Show HN: AI Boost – an MCP for accessing your everyday patterns

 🔍Information Retrieval
ai-boost.io··Hacker News

See what your AI coding agent is doing with Datadog Lapdog

 📞Function Calling
chrisebert.net··Hacker News

Bad MCP design cost your Agent 5× more tokens

 🧠LLM Inference  Content type: Discussion

SIFT: Selective-Index For Fast Compute of RAG Prefill by Exploiting Attention Invariance

 🧠LLMs  Content type: Academic
arxiv.org·

Context Sculpting

 🧩Cognitive Science  Content type: Blog

Claude Fable 5 Launches at #1 on the Artificial Analysis Intelligence Index

 🪨Obsidian  Content type: News

Ask HN: Is it feasible to run a model on device for complete privacy?

 🏠Self-hosting  Content type: Discussion

Tail-Aware Adaptive-k: Query-Adaptive Context Selection for Retrieval-Augmented Generation

 🧠LLMs  Content type: Academic
arxiv.org·

Agentic search - retrieval, harness, or model?

 🔍Information Retrieval  Content type: Blog

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