SCLATE lets benchmarks and agents independently register events through adapters into a shared scheduler.
Shared scheduler enables realistic training of continual-learning agents
SCLATE coordinates benchmark tasks and agent-side events on one accelerated timeline while preserving existing harnesses and memory systems.
Big Tech
Youngmok Jung · Sirajul Salekin · Henry Tran · Javier Movellan · Zhao Huang · Manjot Bilkhu
Apple
Research Digest··2 min read
Thread:Memory Management for Agents
Jung et al.
Why this paper
From Apple · Part of Memory Management for Agents, now 43 papers
In one line
SCLATE enables continual-learning agent evaluation and training by coordinating benchmark and agent events on a shared simulated clock.
What we could check
- ·No code link found
- ·No weights link found
- ·No dataset link found
- ·No compute details found
- ·No stated limitations found
- ✓Reports numbers on named benchmarks (2 benchmarks)
Observed from the paper text and links we have. Absence here means we did not find it, not that it does not exist.
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