Efficiently Updatable Neural Network (NNUE)
beuke.orgยท1d
๐Ÿ“ŠQuantization
Scaling Code-Assisted Chain-of-Thoughts and Instructions for Model Reasoning
arxiv.orgยท21h
โšกIncremental Computation
LaDiR: Latent Diffusion Enhances LLMs for Text Reasoning
arxiv.orgยท21h
๐Ÿ’ปLocal LLMs
Dragon Hatchling: Neural Network That Thinks Like a Brain (and Runs on Your GPU)
medium.comยท13hยท
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๐Ÿ”ฒCellular Automata
Making performant Python bindings to compiled code
kylebarron.devยท10hยท
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๐Ÿฆ€Rust Macros
An alternative to knowledge graphs for storing loosely structured content
fleetingswallow.comยท2dยท
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๐Ÿ•ธ๏ธKnowledge Graphs
Beyond Outcome Reward: Decoupling Search and Answering Improves LLM Agents
arxiv.orgยท21h
โšกProof Automation
A Solution to the Paperclip Problem
link.springer.comยท22hยท
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๐Ÿ”ฒCellular Automata
Towards a Typology of LLM Chains-of-Thought
1a3orn.comยท1dยท
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๐ŸŒณContext free grammars
RAG Chunking Strategies That Actually Work (and Why Most Donโ€™t)
dev.toยท15hยท
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๐Ÿ“„Text Chunking
Delimited Continuations in Lone Lisp
matheusmoreira.comยท4dยท
๐Ÿ”—Lisp
You don't need an AI agent framework, or why frameworks are the new Juicero
konvu.comยท3hยท
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๐Ÿ”ฌRefinement Types
AgentCaster: Reasoning-Guided Tornado Forecasting
arxiv.orgยท21h
โœจEffect Handlers
Thinking on the Fly: Test-Time Reasoning Enhancement via Latent Thought Policy Optimization
arxiv.orgยท21h
๐Ÿ’ปLocal LLMs
Teaching Models to Decide When to Retrieve: Adaptive RAG, Part 4
blog.reachsumit.comยท1dยท
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๐Ÿง Learned Indexing
Latency vs. Accuracy for LLM Apps โ€” How to Choose and How a Memory Layer Lets You Win Both
dev.toยท13hยท
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โšกPerformance Mythology
Transductive and Learning-Augmented Online Regression
arxiv.orgยท21h
๐Ÿ”Information Retrieval
Emergence of Superposition: Unveiling the Training Dynamics of Chain of Continuous Thought
arxiv.orgยท21h
๐Ÿ”ฒCellular Automata