Favoris ; Technical girls and guys ; Representation learning AND LLM
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5 Documents
Jo Kristian Bergum sur X : "...helping people understand the shortcomings of text embedding models for their data. The most powerful has been demonstrating how the embedding models' tokenizers work."
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2024-03-16 About
Nils Reimers sur X : "Embeddings can store only 1 aspect/topic per embedding well."
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2024-03-13 About
Fine-Tuning a Linear Adapter for Any Embedding Model | LlamaIndex Blog | Sep, 2023
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2023-09-18 About
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 About
[2305.12517] Retrieving Texts based on Abstract Descriptions
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2023-06-15 About