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2 results for “mathematical reasoning”
INSPIRE: An Internalize-Then-Improve Approach for Example-Driven Mathematical Reasoning
A new research paper introduces INSPIRE, a two-stage training method for LLMs that aims to improve example-driven mathematical reasoning by first internalizing the strategy and then refining correctness — addressing a gap in how models learn conceptual understanding versus pattern-matching.
Aug 31, 2026
Probing the Origins of Reasoning Performance: Representational Quality for Mathematical Problem-Solving in RL vs. SFT Fine-Tuned Models
A new arXiv preprint investigates why reinforcement learning (RL)-fine-tuned large language models outperform supervised fine-tuned (SFT) models on mathematical reasoning tasks, identifying representational differences in hidden-state structure and layer-wise importance as key mechanistic drivers.
Jul 31, 2026