Essential Chunking Techniques for Building Better LLM Applications
machinelearningmastery.com·1d
📝NLP
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MoM: Mixtures of Scenario-Aware Document Memories for Retrieval-AugmentedGeneration Systems
paperium.net·11h·
Discuss: DEV
🧠RAG
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All You Need to Know About Chunking in Agentic RAG
pub.towardsai.net·3h
📄Document AI
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URL Text Fragments using React Router
developer.mozilla.org·3h·
Discuss: r/reactjs
🧠RAG
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Benchmarking the Most Reliable Document Parsing API
tensorlake.ai·21h·
Discuss: Hacker News
📄Document AI
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"Let's Agree to Disagree": Investigating the Disagreement Problem in Explainable AI for Text Summarization
arxiv.org·10h
🧠RAG
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Self-Attention: The Simple Mechanism That Made ChatGPT Possible
pub.towardsai.net·11h
📝NLP
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GPTF-8: A tokenizer-based character encoding
lesswrong.com·7h
📝NLP
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My dumb prompts that worked better
blog.nilenso.com·3d
📝NLP
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Kindle Notebook export
me.micahrl.com·2h
📝NLP
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Automated Figure-Text Alignment & Knowledge Extraction for Scientific Literature
dev.to·2d·
Discuss: DEV
🎯Vector Search
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Deep learning models simultaneously trained on multiple datasets improve base-editing activity prediction
nature.com·4h
🧠RAG
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Normalized tensor train decomposition
arxiv.org·10h
🎯Vector Search
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Lessons from Implementing RAG in 2025
truestate.io·2d·
Discuss: Hacker News
🧠RAG
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I Use Typst Now
christopherbiscardi.com·14h·
🧠RAG
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Sparse Attention MoE - a test repo for a novel swappable attention mechanism
github.com·2h·
Discuss: r/LocalLLaMA
🤖AI
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From data to corpus: semiotic and documentary issues in audiovisual archives
arxiv.org·10h
📝NLP
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Context Engineering 2.0: The Context of Context Engineering
arxiviq.substack.com·16h·
Discuss: Substack
🕸️Knowledge Graphs
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