Continual learning may work better by feeding ICL the right context, a quoted thread argues
JoshPurtell · x · 2026-07-22
The quoted thread argues that continual learning may be better framed as loading the right information into in-context learning, rather than constantly retraining the model.
The takeaway is that much of a model’s training is really about building the best possible ICL mechanism, and that extra training can degrade knowledge acquisition. The author suggests that, at least for now, memory engineering should focus on the context window—the channel with addresses—rather than on more training. The post points to a paper, with code and data expected soon.
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