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Reinforcement Learning

75 summarised stories about Reinforcement Learning, each linking back to the original source. Browse all topics →

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OpenAI Hugging Face Anthropic DeepSeek DeepSeek R1 NVIDIA

Tuesday, 21 July 2026

Can LLMs invent better ways to train LLMs?

Sakana AI 14

Sakana AI used LLMs to automatically discover new preference optimization algorithms for training other LLMs, a process they call LLM². They discovered Discovered Preference Optimization (DiscoPOP), which outperforms existing methods like DPO across multiple benchmarks. This approach reduces reliance on human researchers to manually design training algorithms and creates a self-referential feedback loop where AI improvements can accelerate future AI development.

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Reinforcement Learning Sakana AI Model Training

The Sequence Knowledge #898: The Trace Is the Teacher: Distilling Reasoning Into Small Models

Substack 1 month ago 43

DeepSeek generated 800,000 worked solutions from its R1 reasoning model and fine-tuned smaller models on these step-by-step traces using standard supervised learning, achieving unexpected success without reinforcement learning or other advanced techniques. The distilled 32B model solved competition math problems significantly harder than expected for its size, while the 7B model developed emergent reasoning abilities like self-verification without explicit training. The approach challenges prior consensus that naive sequence-level imitation cannot work because student models diverge from teacher trajectories at inference time, suggesting that learning from reasoning traces may operate under different principles than simple answer imitation.

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Reinforcement Learning Advanced Reasoning DeepSeek

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