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Research#Policy Optimization🔬 ResearchAnalyzed: Jan 10, 2026 13:26

OptPO: Efficient Test-Time Policy Optimization via Optimal Rollout Allocation

Published:Dec 2, 2025 15:38
1 min read
ArXiv

Analysis

The paper, accessible on ArXiv, presents OptPO, a novel method for test-time policy optimization. This method likely focuses on improving the performance of existing policies during inference.

Key Takeaways

Reference

“The article's context provides no specific details, only mentioning the title and source.”

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