ChronoSSM: training for temporally aware representations in autoregressive state space models
Read the original at arxiv.org→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...
Original headline: "ChronoSSM: Training for Temporally Aware Representations in Autoregressive State Space Models"
Coverage timeline
- Aug 12, 04:00 UTC arXiv cs.LG lead source ChronoSSM: Training for Temporally Aware Representations in Autoregressive State Space Models