GROUNDING

RAG

7 min read

RAG, or retrieval-augmented generation, grounds LLM answers in retrieved documents, code, or data before generation. GROUNDING tracks RAG architecture, retrieval quality, evaluation, grounding failures, and production patterns.

Related: Embeddings Vector Database Hybrid Search Reranking Chunking Context Engineering RAG Evaluation

Recent Updates

  • 2026-06-05: How LLM Agents Work: Architecture, Planning, and Tools (Искусственный интеллект – AI, ANN и иные формы искусственного разума) · habr.com — GPT-5
  • 2026-06-05: llmortem: A Local RAG Service for SRE Documentation and Code (Искусственный интеллект – AI, ANN и иные формы искусственного разума) · habr.com — OpenAI FastAPI Ollama OpenWebUI PagerDuty Grafana Slack GitLab
  • 2026-06-05: Analysis of the Odysseus Self-Hosted AI Workspace (Искусственный интеллект – AI, ANN и иные формы искусственного разума) · habr.com — Alibaba OpenAI Anthropic PewDiePie
  • 2026-06-05: PLC Smart Splitter: Automating Industrial Technical Specification Parsing (Искусственный интеллект – AI, ANN и иные формы искусственного разума) · habr.com — plcstudio GitVerse GitHub OpenAI Anthropic DeepSeek
  • 2026-06-05: Designing an AI Maître d’ for Restaurant Chains: Architecture and Integrations (Искусственный интеллект – AI, ANN и иные формы искусственного разума) · habr.com — IIKO Remarked RocketData
  • 2026-06-05: Why we chose recursive SQL over GraphQL for our knowledge graph (Искусственный интеллект – AI, ANN и иные формы искусственного разума) · habr.com — Google Gemini
  • 2026-06-06: Self-hosting AnythingLLM for business environments (Искусственный интеллект – AI, ANN и иные формы искусственного разума) · habr.com — OpenAI Anthropic Google MikroTik
  • 2026-06-06: PLC AI Studio: Engineering a RAG-based Tool for Industrial Automation Code (Искусственный интеллект – AI, ANN и иные формы искусственного разума) · habr.com — Siemens WAGO ОВЕН
  • 2026-06-06: Google Introduces Agentic RAG Framework for Gemini Enterprise Agent Platform (The latest research from Google) · research.google — Google Google Research Google Cloud Cyrus Rashtchian Da-Cheng Juan Gemini
  • 2026-06-07: Lessons from a Failed Agentic Game Generator Project (Hugging Face - Blog) · huggingface.co — Hugging Face GitHub Nemotron 30b
  • 2026-06-08: EASE-TTT: Evidence-Aligned Selective Test-Time Training for Long-Context Question Answering (cs.AI updates on arXiv.org) · arxiv.org
  • 2026-06-08: SEEK: Steering LLM Reasoning for RAG via Internal Reasoning Sketches (cs.CL updates on arXiv.org) · arxiv.org — Xinze Li
  • 2026-06-08: MemDreamer: Decoupling Perception and Reasoning for Long Video Understanding via Hierarchical Graph Memory and Agentic Retrieval Mechanism (cs.CL updates on arXiv.org) · arxiv.org
  • 2026-06-08: Mind the Gap: Bridging Behavioral Silos with LLMs in Multi-Vertical Recommendations (cs.AI updates on arXiv.org) · arxiv.org — DoorDash
  • 2026-06-08: Evidence Graph Consistency Framework for Hallucination Detection in RAG (cs.AI updates on arXiv.org) · arxiv.org — GPT-4 GPT-3.5 Mistral-7B LLaMA-2
  • 2026-06-08: Your UnEmbedding Matrix is Secretly a Feature Lens for Text Embeddings (cs.CL updates on arXiv.org) · arxiv.org
  • 2026-06-08: SWE-Explore: Benchmarking How Coding Agents Explore Repositories (cs.CL updates on arXiv.org) · arxiv.org
  • 2026-06-08: HKVM-RAG: Key-Value-Separated Hypergraph Evidence Organization for Multi-Hop RAG (cs.CL updates on arXiv.org) · arxiv.org — ColBERTv2
  • 2026-06-08: Principles of Concept Representation in Sentence Encoders (cs.CL updates on arXiv.org) · arxiv.org
  • 2026-06-08: Trading Engagement for Sustainability: Carbon-aware Re-ranking for E-commerce Recommendations (cs.AI updates on arXiv.org) · arxiv.org — Amazon
  • 2026-06-08: Didact: A Cross-Domain Capability Discovery System for Defence (cs.CL updates on arXiv.org) · arxiv.org — arXiv
  • 2026-06-08: MExam: Benchmarking Multimodal Memory for Realistic User-Agent Interactions (cs.CL updates on arXiv.org) · arxiv.org
  • 2026-06-08: Evidence Graph Consistency in Retrieval-Augmented Generation: A Model-Dependent Analysis of Hallucination Detection (cs.CL updates on arXiv.org) · arxiv.org — Meta OpenAI Mistral AI LLaMA-2 GPT-4 GPT-3.5 Mistral-7B
  • 2026-06-08: EASE-TTT: Evidence-Aligned Selective Test-Time Training for Long-Context Question Answering (cs.CL updates on arXiv.org) · arxiv.org
  • 2026-06-08: Evidence-Based Intelligent Diagnostic and Therapeutic Visualization System with Large Language Models: Multi-Turn Interaction and Multimodal Treatment Plan Generation (cs.AI updates on arXiv.org) · arxiv.org — Neo4j
  • 2026-06-08: TA-RAG: Tone-Aware Retrieval-Augmented Generation Framework (cs.CL updates on arXiv.org) · arxiv.org — HIV Online Learning Australia UNAIDS National Association of People with HIV Australia
  • 2026-06-08: MADRAG: Multi-Agent Debate with Retrieval-Augmented Generation for Training-Free Analytic Essay Scoring (cs.CL updates on arXiv.org) · arxiv.org — arXiv
  • 2026-06-08: Explicit Evidence Grounding via Structured Inline Citation Generation (cs.CL updates on arXiv.org) · arxiv.org — arXiv
  • 2026-06-08: Building a Grounded, Citation-Based RAG System Locally (Искусственный интеллект – AI, ANN и иные формы искусственного разума) · habr.com — Ollama Russian Ministry of Sport FIBA CEV Gemma 4 BGE-M3 bge-reranker-v2-m3
  • 2026-06-08: Rebuilding RAG Search for a Helpdesk Assistant: Insights and Optimization (Искусственный интеллект – AI, ANN и иные формы искусственного разума) · habr.com — Bitrix24 Alexey
  • 2026-06-08: AI in Business: Value Creation and Implementation Pitfalls (Искусственный интеллект – AI, ANN и иные формы искусственного разума) · habr.com — GPT-4
  • 2026-06-09: A Multi-Agent System for IPMSM Design Optimization via an FEA-AI Hybrid Approach (cs.AI updates on arXiv.org) · arxiv.org
  • 2026-06-09: Co-Evolving Skill Generation and Policy Optimization (cs.CL updates on arXiv.org) · arxiv.org
  • 2026-06-09: Multilingual Fact-Checking at Scale: Fine-Tuned Compact Models vs LLMs (cs.CL updates on arXiv.org) · arxiv.org — Factiverse XLM-RoBERTa-Large mmBERT-base GPT-5.2 Claude Opus 4.6 Qwen3-8B
  • 2026-06-09: Pharmacogenomic Knowledge Graph Augmentation for Drug-Drug Interaction Prediction (cs.LG updates on arXiv.org) · arxiv.org — PharmGKB
  • 2026-06-09: Customer-Agent: Overcoming Context Limitations in Ultra-Long Shopping Trajectories via Tool-Augmented Agents and RLVR (cs.CL updates on arXiv.org) · arxiv.org
  • 2026-06-09: KITE: A Tri-Modal Transformer Integrating Text, Images, and Knowledge Graphs for Fake News Detection (cs.LG updates on arXiv.org) · arxiv.org — CLIP
  • 2026-06-09: PathPocket: A Multi-modal Agentic Co-pilot for Evidence Grounded Computational Pathology (cs.AI updates on arXiv.org) · arxiv.org
  • 2026-06-09: Evaluating RAG Reliability under Clean, Misleading, and Mixed Retrieval (cs.CL updates on arXiv.org) · arxiv.org
  • 2026-06-09: Decision-Aware Memory Cards: Counterfactual-Inspired Context Selection and Compression for Tool-Using LLM Agents (cs.AI updates on arXiv.org) · arxiv.org — arXiv Opus Qwen Codex GPT 5.5 Qwen-QLoRA Qwen3.6-Plus Gemini-3.1-Pro-High Qwen3.5-122B-A10B
  • 2026-06-09: AgentTrust: A Self-Improving Trust Layer for AI-Agent Actions (cs.AI updates on arXiv.org) · arxiv.org
  • 2026-06-09: Retrieval Augmented Generation Framework for the Nepali Legal Domain Question Answering (cs.CL updates on arXiv.org) · arxiv.org — Nepal Kanun Patrika multilingual E5
  • 2026-06-09: TLRD: Teaching LLMs to Reason over Tabular Data with Tri-Level Rationale Distillation (cs.CL updates on arXiv.org) · arxiv.org
  • 2026-06-09: TrustMargin: Arbitration Between Parametric Memory and Retrieved Evidence (cs.CL updates on arXiv.org) · arxiv.org — LLaMA
  • 2026-06-09: Pathway Live Data Framework for Stream Processing and RAG Pipelines (GitHub AI Ranking Changes (Top 10)) · github.com — Kafka Google Microsoft PostgreSQL SharePoint Airbyte Mistral AI GPT-4o
  • 2026-06-09: Analyzing the Claude Code Best Practices Repository (Все статьи подряд / Искусственный интеллект / Хабр) · habr.com — Anthropic GitHub Boris Cherny shanraisshan Claude
  • 2026-06-09: Building an Advanced RAG Pipeline for Corporate AI Assistants (Все статьи подряд / Искусственный интеллект / Хабр) · habr.com — Confluence Jira GitLab Саша
  • 2026-06-09: AI Mentions Are Not Trust: How to Build Substantive Content for AI Retrieval (Все статьи подряд / Искусственный интеллект / Хабр) · habr.com — Burson Ivan Ivanych
  • 2026-06-09: Is Grep All You Need? How Agent Harnesses Reshape Agentic Search (Hacker News) · arxiv.org
  • 2026-06-09: Optimizing for AI: Generative Engine Optimization (GEO) strategies (Все статьи подряд / Искусственный интеллект / Хабр) · habr.com — Geozr.com Alisa AI Perplexity Google Schema.org Habr Cossa VC.ru Spark Petr Grishechkin

FAQ

What is RAG?

RAG, or retrieval-augmented generation, grounds LLM answers in retrieved documents, code, or data before generation. GROUNDING tracks RAG architecture, retrieval quality, evaluation, grounding failures, and production patterns.

Related concepts tracked by the radar include Embeddings, Vector Database, Hybrid Search, Reranking, Chunking.

What does this RAG page track?

Dated updates, papers, and mentions of RAG collected by the GROUNDING radar, most recently on 2026-06-09.

Graph View

Backlinks