Sebastian Raschka
ML research & education
AI researcher, author of "Machine Learning with PyTorch and Scikit-Learn". Staff ML at Lightning AI.
Recent activity
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Controlling Reasoning Effort in LLMs
How LLMs Learn Low-, Medium-, and High-Effort Reasoning Modes
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Using Local Coding Agents
Using Open-Weight Models in Local Coding Harnesses as an Alternative to Claude Code and Codex Subscriptions
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LLM Research Papers: The 2026 List (January to May)
A curated roundup of notable LLM research papers that came out this year
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Recent Developments in LLM Architectures: KV Sharing, mHC, and Compressed Attention
From Gemma 4 to DeepSeek V4, How New Open-Weight LLMs Are Reducing Long-Context Costs
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My Workflow for Understanding LLM Architectures
A learning-oriented workflow for understanding new open-weight model releases
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Components of A Coding Agent
How coding agents use tools, memory, and repo context to make LLMs work better in practice
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A Visual Guide to Attention Variants in Modern LLMs
From MHA and GQA to MLA, sparse attention, and hybrid architectures
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A Dream of Spring for Open-Weight LLMs: 10 Architectures from Jan-Feb 2026
A Round Up And Comparison of 10 Open-Weight LLM Releases in Spring 2026
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Categories of Inference-Time Scaling for Improved LLM Reasoning
And an Overview of Recent Inference-Scaling Papers
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The State Of LLMs 2025: Progress, Problems, and Predictions
A 2025 review of large language models, from DeepSeek R1 and RLVR to inference-time scaling, benchmarks, architectures, and predictions for 2026.
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