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Large reasoning models (LRMs) have achieved remarkable progress on complex tasks by generating extended chains of thought (CoT).
Proximal policy optimization algorithms
John Schulman, Filip Wolski, Prafulla Dhariwal, Alec Radford, and Oleg Klimov · 2017
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Precise length control in large language models, 2024
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Rlhf workflow: From reward modeling to online rlhf
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L1: Controlling how long a reasoning model thinks with reinforcement learning
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Deepseekmath: Pushing the limits of mathematical reasoning in open language models
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