arXiv Machine Learning August 12, 2026 By Adrien Schoen, Nachiketa Ratnakar Patil, Arjun Bhagoji, Francesco Bronzino

ChronoSSM: Training for Temporally Aware Representations in Autoregressive State Space Models

Read the original on arXiv Machine Learning →

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.

Summary generated by The Flow from the publisher's feed. The full article lives at arXiv Machine Learning.

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