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The Transformer Architecture: A Deep Dive into How LLMs Actually Work
dev.to·7h·
Discuss: DEV
📝Text Parsing
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Natural language processing for word sense disambiguation and information extraction
arxiv.org·19h·
Discuss: r/compsci
📥Feed Aggregation
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TRUNAJOD: A text complexity library for text analysis built on spaCy — TRUNAJOD 0.1.1 documentation
trunajod20.readthedocs.io·12h
📝Parsing Grammars
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Learning Zig
blog.senko.net·7h
🌳Incremental Parsing
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Stanford CS 224N | Natural Language Processing with Deep Learning
web.stanford.edu·1d
🧠Machine Learning
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ECP-Solutions/ASF: The first embeddable scripting language and runtime that turns VBA into a script host (with NO COM dependencies) , with C-like syntax, closures, FFI for VBA calls, and the powerfull VBA-Expressions math integration.
github.com·9h·
Discuss: Hacker News
🦀Rust Macros
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Show HN: Languagecat, a free dataset for people making language-learning apps
language.cat·4d·
Discuss: Hacker News
📝Text Parsing
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Self-Supervised Temporal Pattern Mining for circular manufacturing supply chains with embodied agent feedback loops
dev.to·6h·
Discuss: DEV
🌊Stream Processing
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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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Exploring TabPFN: A Foundation Model Built for Tabular Data
towardsdatascience.com·12h
📝ABNF Parsing
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I’m an AI expert – here are my top 5 secret tools that could change your life in 2026
techradar.com
·16h
🎯Content Recommendation
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Voices from the Past: Retrieval-Augmented Dialogues with Chinese Historical Figures
digitalorientalist.com·1d
🏛Digital humanities
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The 2025 Guide to Machine Learning
ibm.com·1d·
Discuss: Hacker News
🧠Machine Learning
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Training a Model on Multiple GPUs with Data Parallelism
machinelearningmastery.com·1d
⚡Parallel Computing
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A Validated Semantics for LLVM IR
sf.snu.ac.kr·16h
✅Formal Methods
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Demystifying Fuzzer Behaviour (39c3)
cdn.media.ccc.de·13h
🐛Fuzzing
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AI Has Made it Easy to Own Your Tools
jimmyhmiller.github.io·1d
🤖Archive Automation
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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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Book Review: Why Machines Learn
philippdubach.com·1d·
Discuss: Hacker News
🧠Machine Learning
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Document Parsing with LLMs: From OCR to Structural Understanding.
alamedadev.com·3d
📋Document Grammar
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