SCLATE: A Substrate for Continual-Learning Agent Training and Evaluation
Continual-learning agents are systems of models, harnesses, and memory operating over long multi-session horizons. Evaluating and training them requires interleaving tasks with age
Virticle Desk · Edited to Virticle Standards
September 30, 2026
4 minute read
The human is the plot.
In short: SCLATE: A Substrate for Continual-Learning Agent Training and Evaluation
What moved
SCLATE: A Substrate for Continual-Learning Agent Training and Evaluation - Apple Machine Learning Research SCLATE: A Substrate for Continual-Learning Agent Training and Evaluation Authors Youngmok Jung, Sirajul Salekin, Henry Tran, Javier Movellan, Zhao Huang, Manjot Bilkhu Continual-learning agents are systems of mode
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Ask what default, power relation, or daily ritual actually changed. If the answer is still “a demo,” this would not ship on Friday either.
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Source → Apple Machine Learning Research
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