Tag
GRPO
Every GRPO story we've curated in Bowl of Data, newest issue first — part of our weekly digest across AI, security, blockchain, and engineering.
Week 29 · 2026
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Ring-Zero: Scaling Zero RL to a Trillion Parameters for Emergent Reasoning
This paper presents the development of Ring-2.5-1T-Zero, a trillion-parameter model trained via zero-shot reinforcement learning to elicit emergent reasoning. The study validates that massive scaling enables models to spontaneously develop complex problem-solving strategies like self-verification without human-annotated data.
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Ring-Zero: Scaling Zero RL to a Trillion Parameters for Emergent Reasoning
This paper presents the development of Ring-2.5-1T-Zero, a trillion-parameter model trained via zero-shot reinforcement learning to elicit emergent reasoning. The study validates that massive scaling enables models to spontaneously develop complex problem-solving strategies like self-verification without human-annotated data.
Week 27 · 2026
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Is One Layer Enough? Training A Single Transformer Layer Can Match Full-Parameter RL Training
This study demonstrates that reinforcement learning post-training for LLMs is not a uniform process across all parameters but is concentrated in specific middle layers. By leveraging this discovery, researchers developed layer-aware training methods that outperform traditional full-parameter optimization.
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Is One Layer Enough? Training A Single Transformer Layer Can Match Full-Parameter RL Training
This study demonstrates that reinforcement learning post-training for LLMs is not a uniform process across all parameters but is concentrated in specific middle layers. By leveraging this discovery, researchers developed layer-aware training methods that outperform traditional full-parameter optimization.
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