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Research#Reasoning🔬 ResearchAnalyzed: Jan 10, 2026 11:19

Reasoning Models: Unraveling the Loop

Published:Dec 15, 2025 00:44
1 min read
ArXiv

Analysis

This ArXiv paper likely delves into the undesirable looping behavior observed in reasoning models. Understanding and mitigating these loops is crucial for improving the reliability and efficiency of AI systems.
Reference

“The article's context points to an examination of looping behavior in reasoning models.”

PermalinkArXiv
Research#llm📝 BlogAnalyzed: Jan 3, 2026 06:56

The State of LLM Reasoning Model Inference

Published:Mar 8, 2025 12:11
1 min read
Sebastian Raschka

Analysis

The article focuses on inference-time compute scaling methods for improving reasoning models. This suggests a technical focus on optimizing the performance of Large Language Models (LLMs) during the inference phase, which is crucial for real-world applications. The source, Sebastian Raschka, is a known figure in the field, adding credibility to the information.
Reference

“Inference-Time Compute Scaling Methods to Improve Reasoning Models”

PermalinkSebastian Raschka