Research proposes dynamic compression for in-context continual learning
HanGuo97 · x · 2026-08-21
This tweet discusses the trend towards in-context continual learning and introduces research on dynamically compressing information for future retrieval. It notes that RNNs compress growing history into a fixed-size state with a single write per token. The work explores dynamic compression: allowing models to revisit and reorganize their state as they discover what needs to be reused.
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