Technology ❯ Artificial Intelligence ❯ Machine Learning ❯ Natural Language Processing

Retrieval-Augmented Generation

RAG Research Delivers New Benchmark and Clear Guidance on Retrieval, Reasoning, and Bias

New empirical results point teams toward measured, simpler retrieval with targeted augmentation when metrics justify complexity.

Two arXiv Preprints Propose Adaptive RAG With Complexity Scoring and Agentic Retrieval

Agentic RAG Gains Traction as Practitioners Map the Path to Production

New RAG Research Debuts Adaptive Retrieval Advances as Security Risks Emerge

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