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How LLMs Actually Work: A Friendly Map for Humans • oreoro

 💬Natural Language Processing

Benchmarking Large Language Models for Safety Data Extraction

 🤖AI Agents  Content type: Academic
arxiv.org·

Show HN: LLM memory without context bleed; 100% precision vs. <10% vector search

 🔍Information Retrieval

Running Qwen 35B MoE at 450k Context on a Single 32GB GPU

 🧠LLM Inference
Less-relevant results

Introducing GitLab Orbit

 🧠LLMs  Content type: Blog

Prompt Injection in RAG Agentic Systems

 🧠LLMs
ulad.net··Hacker News

Show HN: Bosun – a small model that keeps an agent's memory graph clean

 🎯Fine-tuning
huggingface.co··Hacker News

Researchers trained an open source AI search agent, Harness-1, that outperforms GPT-5.4 on recalling relevant information

 🎮Reinforcement Learning

When Poison Fails After Retrieval: Revisiting Corpus Poisoning under Chunking and Reranking Pipelines

 🔍Information Retrieval  Content type: Academic
arxiv.org·

Show HN: Run Llama.cpp In-Process from Java with Project Panama FFM

 🧠LLM Inference

ashp15205/guardian-runtime: A zero-latency, local-first runtime firewall for LLMs. Intercept every prompt and response locally to stop data leaks and runaway token costs.

 🧠LLMs  Content type: Code

Show HN: Audit any AI/data pairing with Veritrooper

 🧠LLMs

The AI Curse (Vis the Lisp Curse)

 🧠LLMs  Content type: Blog

CompRank: Efficient LLM Reranking via Token-Level Compression and Decoding-Free Scoring

 🔍Information Retrieval  Content type: Academic
arxiv.org·

Tool to convert technical PDFs into RAG-ready chunks and Obsidian vaults

 🪨Obsidian

Is your agent extension actually working?

 🤖Machine Learning  Content type: Blog

Engineers building MCPs in regulated industries: what's been the hardest part?

 🧠LLMs
deepsense.ai··Hacker News

hashwnath/KMCP: Open-source MCP server for your docs. Zero LLM at query time. docker compose up and go.

 🏠Self-hosting  Content type: Code
github.com··Hacker News

Sales Is the Customer Clock

 🧠LLMs
hari.computer··Hacker News

memory OS for AI agents (ranks, compresses and evolves agents memory)

 🔍Information Retrieval

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