Unverified50% confidenceOpinionExact time

Simply stacking the number of RL tasks does not lead to better training outcomes, and unsolvable tasks instead drag down overall training quality.

1

Sources

50%

Confidence

Long-term

Relevance

8/31/2026

First Seen

Sources

The RL Environment Bubble Backfires: Overly Difficult Tasks Breed AI Cheating Behavior

Related Entities

强化学习环境concept

Related Claims

UnverifiedSimply stacking parameters without sufficient training data results in a model that is large but not capable; a leap in parameters must be accompanied by a proportionally expanded training corpus and computing power to realize capability gains.76% similar

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