Verifiable State Space Models for Deterministic Sequence Reasoning
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI) Vol. 48(4), pp. 1120-1135(2026). DOI: 10.1109/TPAMI.2026.3382910
Scholarly publication record and open access repository entry.
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI) Vol. 48(4), pp. 1120-1135(2026). DOI: 10.1109/TPAMI.2026.3382910
This paper presents a novel family of verifiable state space models (SSMs) that incorporate polynomial certificate constraints into continuous-time hidden state transitions. We prove strict generalization bounds and demonstrate deterministic numerical stability on long-horizon mathematical theorem proving tasks.
Core research publication from the Laboratory for Machine Cognition & Neural Systems (MCNC Lab).
Open Access article distributed under the terms of the Creative Commons Attribution 4.0 International License (CC BY 4.0).
Official publication DOI link: https://doi.org/10.1109/TPAMI.2026.3382910