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Natural language processing for word sense disambiguation and information extraction
arxiv.org·14h·
Discuss: r/compsci
📥Feed Aggregation
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🧠 Beyond Chatbots: Building 'Echo-Learn', an Agentic AI Tutor with Biological Memory
dev.to·1d·
Discuss: DEV
🎙️Whisper
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faradayio/xsv2: Fork of xsv because qsv is too much
github.com·7h·
Discuss: Hacker News
🗜️LZSS Variants
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AI Has Made it Easy to Own Your Tools
jimmyhmiller.github.io·1d
🤖Archive Automation
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TRUNAJOD: A text complexity library for text analysis built on spaCy — TRUNAJOD 0.1.1 documentation
trunajod20.readthedocs.io·7h
📝Parsing Grammars
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SMART SLM: Structured Memory and Reasoning Transformer, A Small Language Model for Accurate Document Assistance
arxiv.org·2d
📋Document Grammar
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Meta brings Segment Anything to audio, letting editors pull sounds from video with a click or text prompt
the-decoder.com·1d
🎧Audio Restoration
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Document Parsing with LLMs: From OCR to Structural Understanding.
alamedadev.com·3d
📋Document Grammar
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The Transformer Architecture: A Deep Dive into How LLMs Actually Work
dev.to·2h·
Discuss: DEV
📝Text Parsing
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vagos/llm-grep: Match lines using both classic and semantic regular expressions with LLM.
github.com·1d·
Discuss: Lobsters
🔍RegEx Engines
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I built a production-ready document parser for RAG apps that actually handles complex tables (full tutorial + code)
dev.to·1d·
Discuss: DEV
📋Document Grammar
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Do we need semantic layer anymore? What are the limitations of LLMs?
motherduck.com·3d·
Discuss: Hacker News
🧮Datalog
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aashirpersonal/semantic-coverage: Automated detection of knowledge gaps and blind spots in RAG vector stores.
github.com·3d·
Discuss: Hacker News
🌀Brotli Internals
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Joint 2D-3D-Semantic Data for Indoor Scene Understanding
dev.to·1h·
Discuss: DEV
🌐Archive Topology
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Benchmarking and Enhancing VLM for Compressed Image Understanding
arxiv.org·2d
🧠Learned Compression
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The 2025 Guide to Machine Learning
ibm.com·1d·
Discuss: Hacker News
🧠Machine Learning
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Building an AI Document Processing Pipeline on AWS (Textract + Bedrock)
dev.to·10h·
Discuss: DEV
🔄Archival Workflows
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CASA: Cross-Attention via Self-Attention
kyutai.org·3d·
Discuss: Hacker News
🗜️LZW Variants
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Unifying Visual-Semantic Embeddings with Multimodal Neural Language Models
dev.to·19h·
Discuss: DEV
🧮Vector Embeddings
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Stanford CS 224N | Natural Language Processing with Deep Learning
web.stanford.edu·1d
🧠Machine Learning
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