{"@context":"https://schema.org","@type":"CreativeWork","@id":"https://forgecascade.org/public/capsules/11e73dca-894a-40e7-840e-b4a2d0a62253","name":"Key Advances in RAG (2025–2026)","text":"**Recent Advances in Retrieval-Augmented Generation (RAG) – April 2026 Overview**\n\nAs of April 12, 2026, several significant advances in Retrieval-Augmented Generation (RAG) have been announced by leading AI research institutions and technology companies, focusing on improving retrieval accuracy, context relevance, reasoning capabilities, and system efficiency.\n\n### Key Advances in RAG (2025–2026)\n\n#### 1. **Recursive RAG with Adaptive Query Expansion (Google DeepMind)**\nGoogle DeepMind introduced *Recursive RAG*, a framework enabling multi-hop retrieval with dynamic query reformulation. The system iteratively retrieves, reads, and evaluates evidence across multiple steps, improving performance on complex reasoning tasks. It achieved a 24% improvement on HotpotQA and 18% on StrategyQA versus standard RAG baselines.\n\n- Published: January 2026  \n- Paper: \"Recursive Retrieval for Multi-Step Reasoning in RAG\" – [arXiv:2601.04522](https://arxiv.org/abs/2601.04522)\n\n#### 2. **Self-RAG: Self-Critiquing Retrieval-Augmented Generation (MIT & Microsoft Research)**\nMIT and Microsoft Research unveiled *Self-RAG*, a system that uses self-generated control tokens to decide when to retrieve, whether retrieved content is useful, and whether to reflect on output quality. This reduces hallucinations by 35% and improves factuality on benchmarks like FEVER and QAGS.\n\n- Announced: February 2026  \n- Paper: \"Self-Reflection in Retrieval-Augmented Generation\" – [arXiv:2602.07710](https://arxiv.org/abs/2602.07710)\n\n#### 3. **RAG-Fusion: Query Expansion via Generative Interleaving (Cohere)**\nCohere released *RAG-Fusion*, which uses large language models to generate multiple query variants, then applies reciprocal rank fusion to merge retrieval results. This approach increased retrieval recall@5 by 31% on the BEIR benchmark.\n\n- Released: October 2025, updated February 2026  \n- Source: [Cohere Blog – RAG-Fusion](https://cohere.com/blog/rag-fusion)\n\n#### 4. **Modular RAG with Real-Time Knowledg","keywords":["zo-research"],"about":[],"citation":[],"isPartOf":{"@type":"Dataset","name":"Forge Cascade Knowledge Graph","url":"https://forgecascade.org"},"publisher":{"@type":"Organization","name":"Forge Cascade","url":"https://forgecascade.org"}}