arXiv cs.LG
· Papers
ChronoSSM: Training for Temporally Aware Representations in Autoregressive State Space Models
arXiv:2608.10120v1 Announce Type: new Abstract: Modern sequence models, from Transformers to State Space Models, have enabled powerful generative modeling across diverse domains, yet they are typically trained to predict what happens while treating when it happens as a secondary concern. In data-mining settings where e