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๐Ÿ“‹ Document Grammar

Structure Parsing, Format Specification, ABNF Extensions, Schema Languages

Highlights from UTC Meeting #184
blog.unicode.orgยท2d
๐ŸŒCharacter Sets
Whatโ€™s wrong with the JSON gem API?
byroot.github.ioยท13h
โœ…Format Verification
A language model built for the public good
jmason.ieยท2d
๐Ÿ’ปLocal LLMs
The Illusion of Thought
wormsandviruses.comยท3h
๐ŸŒฑPersonal Wikis
Changing of the guard: Anthropic new AI market leader among US companies
heise.deยท14h
๐Ÿ”„Language Evolution
React Compiler Is Coming
thenewstack.ioยท8h
๐Ÿ”„Language Evolution
[P] A Black Box LLM Explainability Metric
reddit.comยท3dยท
Discuss: r/MachineLearning
๐Ÿง Intelligence Compression
Introduction to Supervised Machine Learning for Beginners
dev.toยท14hยท
Discuss: DEV
๐Ÿง Machine Learning
Investigating the Invertibility of Multimodal Latent Spaces: Limitations of Optimization-Based Methods
arxiv.orgยท1d
๐Ÿง Machine Learning
Argumentatively Coherent Judgmental Forecasting
arxiv.orgยท1d
๐Ÿ“ŠFeed Optimization
Proto-EVFL: Enhanced Vertical Federated Learning via Dual Prototype with Extremely Unaligned Data
arxiv.orgยท2d
๐Ÿง Machine Learning
High-Performance Code Analysis Engine for Claude Code in C++17
dev.toยท2dยท
Discuss: DEV
๐Ÿ”จCompilers
The Self-Improving Prompt System That Gets Smarter With Every Use - And Anyone Can Master
dev.toยท13hยท
Discuss: DEV
โšกProof Automation
Code with LLMs and a Plan
richstone.ioยท1dยท
Discuss: Hacker News
โš”๏ธLean Tactics
Efficient Differentially Private Fine-Tuning of LLMs via Reinforcement Learning
arxiv.orgยท2d
๐Ÿ’ปLocal LLMs
StepFun Built an Efficient and Cost-Effective LLM Storage Platform with JuiceFS
dev.toยท1dยท
Discuss: DEV
๐ŸŒŠStreaming Systems
The Agentic Web Needs a Protocol
dev.toยท1dยท
Discuss: DEV
๐ŸŒWeb Standards
A Markov Categorical Framework for Language Modeling
arxiv.orgยท5d
๐ŸงฎKolmogorov Complexity
Survey of NLU Benchmarks Diagnosing Linguistic Phenomena: Why not Standardize Diagnostics Benchmarks?
arxiv.orgยท4d
โš™๏ธCompression Benchmarking
Investigating Structural Pruning and Recovery Techniques for Compressing Multimodal Large Language Models: An Empirical Study
arxiv.orgยท4d
๐Ÿง Machine Learning
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