Retriever AND Jerry Liu
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23 Documents
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 A propos
Jerry Liu sur X : "a big step towards better RAG... is to just have a really nice PDF parser. It’s so important because a good parser unlocks way more interesting indexing/retrieval strategies…"
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2024-02-23 A propos
Jerry Liu sur X : "Build a RAG backend over any website in a single CLI command ..."
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2024-02-03 A propos
Jerry Liu sur X : "4 Levels of Agents for RAG..."
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2024-01-23 A propos
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 A propos
Jerry Liu sur X : "Naive chunking strategies cause poor RAG performance...."
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2023-12-06 A propos
Jerry Liu sur X : "There's different ways you can parse embedded tables for RAG..."
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2023-12-02 A propos
Jerry Liu sur X : "Advanced RAG architectures need to implement dynamic retrieval..."
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2023-10-22 A propos
Jerry Liu sur X : "Using LLMs for automated decision making (routing) is a huge part of an advanced RAG/agent app But LLMs are expensive and slow... Fine-tune embeddings instead"
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2023-10-19 A propos
Jerry Liu sur X : "The idea of “small-to-big” retrieval: - retrieve on smaller pieces, expand into more context for LLM synthesis..."
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2023-10-02 A propos
Jerry Liu sur X : "evaluating RAG: purely evaluating retrieval metrics (MRR, precision) isn’t the whole picture - you need end-to-end response evals..."
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2023-09-26 A propos
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 A propos
Jerry Liu sur X : "how do you get a good retrieval dataset w/o spending a ton of money on human labels? Answer: use LLMs"
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2023-08-30 A propos
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 A propos
Jerry Liu sur X : "One major way to improve your RAG system is to fine-tune your embedding model"
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2023-08-25 A propos
Jerry Liu sur X : "8 key considerations for building *production-grade* LLM apps over your data (RAG)..."
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2023-08-20 A propos
Jerry Liu on X: “Graph RAG” in @llama_index: a new method of augmenting LLMs with context from a graph database
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2023-08-17 A propos
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 A propos
Jerry Liu sur Twitter : "Using cross-encoding as a reranking step can dramatically speed up LLM inference time AND improve accuracy!"
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2023-07-20 A propos
Jerry Liu sur Twitter : Hot take: if you want to... deliver technical differentiation, you will need to learn LLM development in a “bottoms-up” fashion
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2023-07-16 A propos
Jerry Liu sur Twitter : "If you’re building “chat over your PDFs” with LLMs, you need to deal with the pesky issue of how to parse embedded tables/diagrams..."
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2023-07-07 A propos
Jerry Liu sur Twitter : "The DSP project carries a lot of insights for improving RAG..."
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2023-06-18 A propos
Jerry Liu sur Twitter : "Tuning top-k for semantic search is challenging... Introducing the LlamaIndex AutoRetriever for vector databases"
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2023-05-13 A propos