GPT-6 Astra, Looped Transformers, and Hidden Reasoning
再帰的深さ、隠れた推論、ループを探る…
Sebastian Raschka, PhD 著
Intel · ソース
Ahead of AI
radar が Ahead of AI から拾ったすべての情報、新しい順。
21 件を収集済み
How Claude Watermarks AI-Generated Text
A 48-minute video walkthrough of token sampling, watermark detection, and removal
Sebastian Raschka, PhD 著Building an AI Text Detector From Scratch
An End-to-End Project With Dataset Construction, Model Training, Local Deployment, and RLVR
Sebastian Raschka, PhD 著Controlling Reasoning Effort in LLMs
How LLMs Learn Low-, Medium-, and High-Effort Reasoning Modes
Sebastian Raschka, PhD 著Using Local Coding Agents
Using Open-Weight Models in Local Coding Harnesses as an Alternative to Claude Code and Codex Subscriptions
Sebastian Raschka, PhD 著LLM Research Papers: The 2026 List (January to May)
A curated roundup of notable LLM research papers that came out this year
Sebastian Raschka, PhD 著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
Sebastian Raschka, PhD 著My Workflow for Understanding LLM Architectures
A learning-oriented workflow for understanding new open-weight model releases
Sebastian Raschka, PhD 著Components of A Coding Agent
How coding agents use tools, memory, and repo context to make LLMs work better in practice
Sebastian Raschka, PhD 著A Visual Guide to Attention Variants in Modern LLMs
From MHA and GQA to MLA, sparse attention, and hybrid architectures
Sebastian Raschka, PhD 著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
Sebastian Raschka, PhD 著Categories of Inference-Time Scaling for Improved LLM Reasoning
And an Overview of Recent Inference-Scaling Papers
Sebastian Raschka, PhD 著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.
Sebastian Raschka, PhD 著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.
Sebastian Raschka, PhD 著From DeepSeek V3 to V3.2: Architecture, Sparse Attention, and RL Updates
Understanding How DeepSeek's Flagship Open-Weight Models Evolved
Sebastian Raschka, PhD 著Beyond Standard LLMs
Linear Attention Hybrids, Text Diffusion, Code World Models, and Small Recursive Transformers
Sebastian Raschka, PhD 著Understanding the 4 Main Approaches to LLM Evaluation (From Scratch)
Multiple-Choice Benchmarks, Verifiers, Leaderboards, and LLM Judges with Code Examples
Sebastian Raschka, PhD 著Understanding and Implementing Qwen3 From Scratch
A Detailed Look at One of the Leading Open-Source LLMs
Sebastian Raschka, PhD 著From GPT-2 to gpt-oss: Analyzing the Architectural Advances
And How They Stack Up Against Qwen3
Sebastian Raschka, PhD 著The Big LLM Architecture Comparison
From DeepSeek-V3 to Kimi K2: A Look At Modern LLM Architecture Design
Sebastian Raschka, PhD 著LLM Research Papers: The 2025 List (January to June)
A topic-organized collection of 200+ LLM research papers from 2025
Sebastian Raschka, PhD 著