Unverified50% confidenceFactExact time
分配给预训练的算力越多，下游任务的pass@1奖励就越高，预训练损失越低模型在后续RL中获得的收益越大
1
Sources
50%
Confidence
Long-term
Relevance
8/13/2026
First Seen
Sources
Related Claims
Unverified小版本号跃迁通常对应后训练（Post-Training）阶段的优化，而非预训练的重新训练73% similarUnverifiedMethods for addressing overfitting include increasing training data, regularization, early stopping, and Dropout.71% similarVerifiedThrough higher-quality training data, more optimized training strategies, and more refined post-training alignment, smaller-scale models can fully surpass larger-scale but lower-quality-trained models on practical tasks.70% similar
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