Tweet AND RAG (Retrieval-Augmented Generation)
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27 Documents
LlamaIndex 🦙 sur X : "brand-new course on Building Agentic RAG with LlamaIndex with @DeepLearningAI + @AndrewYNg..."
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2024-05-09 A propos
LlamaIndex 🦙 sur X : "An emerging technique to better represent your data for RAG/LLM applications is to only chunk the data, but also hierarchically cluster and index it..."
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2024-03-30 A propos
LlamaIndex 🦙 sur X : "RAFT - Retrieval Augmented Fine Tuning..."
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2024-03-28 A propos
Akshay 🚀 sur X : "Let's build a "Chat with your code" RAG application, step-by-step"
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2024-03-09 A propos
Hrishi sur X : "RAPTOR is... one of the very few [RAG architectures] that actively presumes and uses the structure in a document...."
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2024-03-09 A propos
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 : "Build a RAG backend over any website in a single CLI command ..."
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2024-02-03 A propos
LlamaIndex 🦙 sur X : "Use RAG to build advanced text-to-SQL..."
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2024-01-24 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
Ravi Theja sur X : "Propositions as Chunks to Improve RAG Performance with @llama_index..."
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2024-01-02 A propos
Jerry Liu sur X : "Naive chunking strategies cause poor RAG performance...."
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2023-12-06 A propos
LlamaIndex 🦙 sur X : "A big issue with RAG is that stuffing more context ≠ better...
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2023-11-07 A propos
Rohan sur X : "Multi Document Agent architecture (v0) in @llama_index... allows answering broader set of questions over multiple documents..."
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2023-10-02 A propos
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 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 : "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
Hugging Face sur Twitter : "Transformers release of the Retrieval-Augmented Generation model in collaboration with @facebookai!"
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2021-02-23 A propos