Extension for Visual Studio Code - Ask coding questions inline and get answers in the format of a Stack Overflow thread — condensed, multiple competing answers, one accepted.

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A 41 TB filesystem, two kernels that didn't know about each other, and the ~320 KB of writes that brought it all back.

Inspired by the role of sleep in biological continual learning, we introduce RVW, a trans- former architecture for online continual adaptation of pretrained models. RVW maintains a small pool of per-layer experts that grow and prune in response to distribution shift, with no replay buffer and no explicit task identifier. Applied to TinyLlama-1.1B on a 15,000- chunk six-domain stream, RVW reaches 40 average held-out PPL, substantially better than EWC (158), fine-tuning (164), and LoRA (448) on the same parameter-matched base, while preserving prior-domain performance. Threshold sweeps suggest a combinatorial encoding reading: domain knowledge appears to be carried by routing patterns across layers rather than by individual specialized experts.