Unverified50% confidenceFactExact time
In the early stage of training, low-TVS and high-TVS items are learned at similar speeds; as training progresses, high-TVS items improve faster.
1
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50%
Confidence
Long-term
Relevance
10/28/2026
First Seen
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Related Claims
UnverifiedThe pattern that high-TVS items perform better on knowledge-intensive tasks is the most robust, even when comparing items of similar difficulty.69% similarUnverifiedOne possible explanation is that high-TVS items correspond to knowledge that appears frequently in a specific time period but is not universally present throughout, and the model may better capture these time-varying knowledge signals in the later stage of pretraining.68% similarUnverifiedThe study proposes the temporal variability score (TVS), defined as the coefficient of variation of a knowledge item's negative log-likelihood across time-point models trained on web snapshots from multiple different years.67% similarUnverifiedIn traditional approaches, reinforcement learning action and observation data is transmitted over ROS topics, which becomes a performance bottleneck during high-frequency training.66% similar
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