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Explore how Retrieval-Augmented Generation systems are vulnerable to Prompt Injection and Corpus Poisoning, and why deployed pipelines face persistent risks.
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Learn about evaluating the generation stage of RAG systems with advanced metrics for faithfulness, answer relevance, and context relevance. Discover how frameworks like RAGAs and ARES use large language models to overcome data bottlenecks, ensuring accurate and reliable AI-driven solutions.- Published on
Learn about evaluation metrics for the retrieval component of a RAG system. Discover how metrics like Precision@k, Recall@k, F1@k, MRR, and MAP can optimize your system's performance. Ensure your RAG pipeline delivers high-quality context for better-generated responses.- Published on
Discover how Retrieval-Augmented Generation (RAG) pipelines can fail and learn about strategies to enhance their robustness. Explore common failure modes, from data ingestion to synthesis, and how to address them. Equip yourself with the knowledge to improve your RAG system's reliability and performance.- Published on
Learn about the fundamentals of RAG pipelines and its key components. Design OpenAI and LLAMA 3-based pipelines with a shared ingestor and Chroma vector database to run experiments on advanced RAG methods and failure modes.