Unverified50% confidenceOpinionExact time
For teams currently doing RLVR training, blindly applying "large batch + square-root scaling" may not be worthwhile; understanding the relative positions of the progress clock and the failure clock is more valuable than simply pursuing a larger batch.
1
Sources
50%
Confidence
Medium-term (~90 days)
Relevance
10/14/2026
First Seen
Valid until: 1/12/2027
Sources
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Related Claims
UnverifiedThe researchers proposed a "two clocks" framework that splits the RLVR training process into two independent timing lines: one measuring the number of samples needed to make progress, and the other measuring the number of samples needed to trigger performance collapse.68% similarUnverified近期研究表明RL（尤其是RLVR）并没有给模型注入大量新知识，而更像是激发和对齐预训练阶段已具备的能力67% similarUnverified在强化学习中，更长的训练时间不等于更好的结果，SAC与DIAYN组合存在策略坍塌风险，性能峰值往往出现在训练中段66% similarUnverifiedMethods such as freezing LLM backbone parameters during the visual alignment training phase, staged training, data ratio replay, and LoRA can mitigate catastrophic forgetting in multimodal training.65% similar
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