Technology ❯ Artificial Intelligence ❯ Machine Learning ❯ Natural Language Processing

Retrieval-Augmented Generation

New RAG Research Debuts Adaptive Retrieval Advances as Security Risks Emerge

Fresh arXiv papers report accuracy gains alongside evidence of serious black-box attack risk.

Pentagon Launches GenAI.mil, Opening Google’s Gemini to 3 Million Users for Unclassified Tasks

New Research Pushes Next‑Gen RAG: Process‑Level RL, Shared‑Space Retrieval, and an SAE Hallucination Detector

RAG Research Moves to Graph, Lightweight, and Agentic Designs as New Benchmarks Steer Fixes

New RAG Research Reports Adaptive Retrieval Gains, Multimodal Retrieval Edge

Two New RAG Preprints Propose Theme-Aligned Hypergraphs and Hierarchical Agents

WinnowRAG and TeaRAG Debut With Promises to Cut RAG Noise and Token Load

New Papers Flag Retrieval as RAG’s Weak Link, Propose Practical Fixes

RAG Advances Spotlight Structured Retrieval Gains and Safety Risks in Agentic RL Search

Enterprises Scale RAG in Production as New Studies Expose Recall Gaps and Offer Targeted Fixes

RAG Research Enters Next Phase With Hybrid Retrieval, Dynamic Graphs, and Context Valuation

New Paper Proposes First Formal Threat Model for RAG Security

LLM-Agent Research Coalesces Around Generalizability, RLVR, and Grounded Retrieval

Adversarial Prompt Attack Puts RAG on Alert as Practitioners Tighten Defenses

New HANRAG Preprint Targets Multi‑hop Noise as RAG Guides Proliferate

New RAG Preprints Propose Retrieval, Reasoning, and Graph Methods to Curb Hallucinations

Local RAG Moves Into Practice With Ollama Guides as Analysts Detail Production Risks

September Research Blitz Reveals LLM Vulnerabilities and Rolls Out Real-World Benchmarks

EASI‑RAG Method Debuts to Speed RAG Deployments in Industrial SMEs