Latest research and updates
Research papers, new tools, best practices, and industry developments in the RAG and generative AI ecosystem.
ClawdBot is an open source personal AI assistant that runs on your own machine. With over 12,000 GitHub stars, it integrates WhatsApp, Telegram, Discord and 50+ services for complete automation.
Complete BEIR 2.0 leaderboard with NDCG@10 scores for all top models. Compare Voyage, Cohere, BGE, OpenAI embeddings on the latest benchmark.
MIT study demonstrates that two-stage retrieval with cross-encoder reranking significantly outperforms single-stage vector search across multiple benchmarks.
Discover how autonomous RAG agents are transforming customer support in 2025 with 85% resolution rates, advanced personalization, and revolutionary multichannel integrations.
How European companies are adopting RAG while respecting personal data regulations. Sovereign solutions and best practices.
In-depth analysis of Gemini 2.0 features relevant to RAG: 2 million token context window, native multimodal capabilities, and simplified integration.
Discover 5 concrete RAG use cases tailored to French SMEs: HR, sales, legal, technical, and training. Real examples, measurable ROI, and simplified implementation.
CLaRa introduces continuous latent reasoning to bridge retrieval and generation, achieving state-of-the-art performance on QA benchmarks
Anthropic's latest model delivers breakthrough improvements in retrieval-augmented generation, with superior context handling and reduced hallucinations for enterprise RAG applications.
Microsoft Research unveils GraphRAG, a novel approach that combines RAG with knowledge graphs to improve contextual understanding
Recent research reveals new document chunking approaches that significantly improve RAG system performance
UC Berkeley researchers introduce DecomposeRAG, an automated query decomposition framework that significantly improves multi-hop question answering.
Anthropic releases Claude 3.5 Sonnet with extended context window, improved citation accuracy, and new RAG-specific features for enterprise applications.
GPT-4.5 Turbo specs: 128K context, 50% cheaper than GPT-4, native retrieval, structured output. Complete API guide and migration tips.
Cohere's new embedding model delivers state-of-the-art performance on MTEB benchmark while reducing dimensions from 1024 to 768, cutting costs and improving speed.
Google Research introduces AutoRAGEval, an automated evaluation framework that reliably assesses RAG quality without human annotation.
Weaviate's new hybrid search engine combines BM25, vector search, and learned ranking in a single optimized index for superior RAG retrieval.
Stanford and DeepMind researchers present MM-RAG, a unified framework for retrieving and reasoning over multiple modalities with 65% accuracy improvement.
Microsoft Research unveils GraphRAG 2.0, featuring improved entity extraction, relationship mapping, and 40% better accuracy on complex multi-hop queries.
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