arXiv cs.CLPaper
Proteus: Incremental Memory Activation for Long-Context Sequence Modeling
The core idea is sound: compress history early when there's pressure, then unlock fresh capacity for incoming context. This is a reasonable improvement for memory-based models and could help with the noisy-context problem in very long sequences. Whether this matters depends on your architecture choice. If you're optimizing a memory model for million-token contexts, Proteus is worth testing. If you're using standard transformer inference or rope, this is incremental.