RAG

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Context Engineering: The Industry’s Growing Awareness of Context’s Critical Role in AI

Context Engineering: The Industry’s Growing Awareness of Context’s Critical Role in AI

Why Context Is Suddenly in the Spotlight. Not long ago, building AI-powered applications often meant obsessing over prompt phrasing or …

SPLADE: Combining Sparse and Semantic Approaches

SPLADE: Combining Sparse and Semantic Approaches

In Information Retrieval (IR), current research focuses on leveraging neural networks to find documents relevant to a query. Earlier …

Sparse Embeddings Demystified: From One-Hot Encoding to BM25

Sparse Embeddings Demystified: From One-Hot Encoding to BM25

This blog article aims to clarify some Information Retrieval (IR) methods related to sparse embeddings (or sparse vectors). We will study …

Reranking in RAG: Enhancing Accuracy with Cross-Encoders

Reranking in RAG: Enhancing Accuracy with Cross-Encoders

Reranking has became a must-have in a Retrieval-Augmented Generation (RAG) stack. This powerful technique enables filtering results from a …