Unlocking Reasoning: A Deep Dive into How LLMs Think

Research#llm📝 Blog|Analyzed: Feb 20, 2026 18:15
Published: Feb 20, 2026 14:55
1 min read
Zenn LLM

Analysis

This article offers a fascinating glimpse into the inner workings of how Large Language Models (LLMs) approach complex problem-solving. It highlights the multi-stage process, from breaking down tasks to exploring multiple reasoning paths and self-correcting, demonstrating the increasing sophistication of AI. The explanation of adjusting "Reasoning Level" is a particularly insightful look at the trade-offs between accuracy, speed, and cost.
Reference / Citation
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"Reasoning level changes primarily adjust the allocation of computational resources during inference (Test-time Compute)."
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Zenn LLMFeb 20, 2026 14:55
* Cited for critical analysis under Article 32.