arXiv cs.LGPaper
Learning Length-Extrapolatable Recurrent Models
This addresses a genuine problem: BPTT fails to teach recurrent models how to work on sequences longer than they saw during training. CST is a targeted fix that doesn't require architecture changes. If it works at scale, recurrent models become competitive with Transformers on long-context tasks. The paper is credible but doesn't show production results yet.