arXiv (OAI Expanded)
open access
Replay in the Silent Degrees of Freedom: Continual Learning Without an Offline Phase
Replay-based continual learning rehearses past data either in an offline phase, during which the agent stops acting, or interleaved with the live stream, where it perturbs the computation serving the current input. An agent that learns in deployment can afford neither. Motivated by local sleep, the
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- Formalizing Forgetting: Theory of Forgetting for Online Continual Learning#1325683
- Beyond Discrete Samples: High Information Density Replay for Efficient Lifelong Person Re-Identification#984880
- Learning Dynamics of Continual Learning: A Unified View of Data Attribution, Forgetting, and Plasticity Loss#1118332
- Forgetting, plasticity, and co-observation: a third facet of continual learning#467150
- Amnesia: A Stealthy Replay Attack on Continual Learning Dreams#615056
Record · ID 1361474
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive