Deep Learning ; RAG: chunking AND Retrieval-based NLP
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8 Documents
Nils Reimers sur X : "Embeddings can store only 1 aspect/topic per embedding well."
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2024-03-13 About
Jerry Liu sur X : "To better augment LLMs with context, it makes a lot of sense to organize context not just as a flat list of text chunks, but as a hierarchy of high-level to low-level details. RAPTOR..."
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2024-03-03 About
LlamaIndex: "Instead of using a global fixed chunk size for RAG, try splitting based on the semantics of the text"
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2024-01-13 About
Jerry Liu sur X : "Naive chunking strategies cause poor RAG performance...."
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2023-12-06 About
Rohan sur X : "smaller chunks are good for capturing semantic meaning and larger ones are good for providing better context. @llama_index AutoMergingRetriever takes it one step further..."
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2023-09-30 About
Jerry Liu sur X : "A simple trick to improve retrieval for RAG 💡: Embed “references” to each text chunk instead of the chunk itself (e.g. smaller chunks, summaries)..."
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2023-09-06 About
Jerry Liu sur X : "This might be the first time ChatGPT (+@jxnlco) helped us come up with a better retrieval algorithm for RAG..."
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2023-08-28 About
Jerry Liu sur Twitter : "Some critical data considerations that you must take into account to make your LLM application production-ready"
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2023-07-23 About