Retrieval Augmented Generation, Vector Databases, Knowledge Retrieval, Context Enhancement

Essential Chunking Techniques for Building Better LLM Applications
machinelearningmastery.comΒ·18h
πŸ“NLP
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You may not need pg_vector, sqlite-vss, etc.
dev.toΒ·1dΒ·
Discuss: DEV
🎯Vector Search
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Indexing sparse vectors with Turso
turso.techΒ·2d
🎯Vector Search
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A brief guide for those who slept (on AI) the last two years
github.comΒ·1dΒ·
Discuss: DEV
πŸ“NLP
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Introducing the File Search Tool in Gemini API
blog.googleΒ·12h
πŸ”Search
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Generative Hints
arxiv.orgΒ·1d
🎯Vector Search
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Accumulating Context Changes the Beliefs of Language Models
lm-belief-change.github.ioΒ·23hΒ·
Discuss: Hacker News
πŸ“NLP
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Bridging Generative and Discriminative Noisy-Label Learning via Direction-Agnostic EM Formulation
arxiv.orgΒ·1h
πŸ€–AI
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Continuous Autoregressive Language Models : Alternate for traditional LLMs, paper by Tencent
reddit.comΒ·16hΒ·
Discuss: r/LocalLLaMA
πŸ“NLP
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LLM vs RAG vs Agent Workbook
byhand.aiΒ·6h
πŸ“‹Contract AI
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Laugh, Relate, Engage: Stylized Comment Generation for Short Videos
arxiv.orgΒ·1h
πŸ“NLP
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The Production Generative AI Stack: Architecture and Components
thenewstack.ioΒ·14h
πŸ“„Document AI
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VeriCoT: Neuro-symbolic Chain-of-Thought Validation via Logical Consistency Checks
arxiv.orgΒ·1h
πŸ“‹Contract AI
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REMIND: Input Loss Landscapes Reveal Residual Memorization in Post-Unlearning LLMs
arxiv.orgΒ·1h
πŸ€–AI
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Charting the future of AI, from safer answers to faster thinking
news.mit.eduΒ·8h
πŸ€–AI
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