Distillation aligns compression mechanisms between full-history and recurrent transformers, enabling linear-time recurrent memory that narrows the performance gap for streaming vision and robotics tasks.
Partially observable reinforcement learning with memory traces.arXiv preprint arXiv:2503.15200, 2025
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.CV 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
Compressing Observation History into Agent Memory: Distilling Transformers into Recurrent Transformers
Distillation aligns compression mechanisms between full-history and recurrent transformers, enabling linear-time recurrent memory that narrows the performance gap for streaming vision and robotics tasks.