#test-time compute

A new study reveals that longer reasoning in large language models can degrade performance by causing distraction, overfitting, and alignment issues, challenging the idea that more computation always leads to better results.

Fractional Reasoning introduces a model-agnostic method to adaptively control reasoning depth in LLMs, enhancing performance and efficiency on complex reasoning tasks.