Language Models for Text Classification: From Bag-of-Words to Jev
A Visual Guide to RNNs, CNNs, Transformers, and Calibration, with Hands-On Experiments on Accuracy and Efficiency
33 min read
← All sources
Ahead of AI
Newsletter by Sebastian Raschka
Ahead of AI focuses on machine learning and AI research and is read by more than 200,000 researchers and practitioners who want to stay ahead in a rapidly evolving field.
5 posts in the last 90 days · newest 29 Sept
GPT-6 Astra, Looped Transformers, and Hidden Reasoning
A Look at Recurrent Depth, Hidden Chains of Thought, and Recent Research on Looping Transformer Blocks
26 min read
How Claude Watermarks AI-Generated Text
A 48-minute video walkthrough of token sampling, watermark detection, and removal
34 min read
Building an AI Text Detector From Scratch
An End-to-End Project With Dataset Construction, Model Training, Local Deployment, and RLVR
Paid
Controlling Reasoning Effort in LLMs
How LLMs Learn Low-, Medium-, and High-Effort Reasoning Modes
25 min read
Using Local Coding Agents
Using Open-Weight Models in Local Coding Harnesses as an Alternative to Claude Code and Codex Subscriptions
27 min read
LLM Research Papers: The 2026 List (January to May)
A curated roundup of notable LLM research papers that came out this year
Paid
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
21 min read
My Workflow for Understanding LLM Architectures
A learning-oriented workflow for understanding new open-weight model releases
Paid
Components of A Coding Agent
How coding agents use tools, memory, and repo context to make LLMs work better in practice
14 min read
A Visual Guide to Attention Variants in Modern LLMs
From MHA and GQA to MLA, sparse attention, and hybrid architectures
18 min read
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
21 min read
Categories of Inference-Time Scaling for Improved LLM Reasoning
And an Overview of Recent Inference-Scaling Papers
Paid
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.
27 min read
LLM Research Papers: The 2025 List (July to December)
In June, I shared a bonus article with my curated and bookmarked research paper lists to the paid subscribers who make this Substack possible.
Paid
From DeepSeek V3 to V3.2: Architecture, Sparse Attention, and RL Updates
Understanding How DeepSeek's Flagship Open-Weight Models Evolved
24 min read
Beyond Standard LLMs
Linear Attention Hybrids, Text Diffusion, Code World Models, and Small Recursive Transformers
30 min read