State Space Models

Also known as SSM

State space models describe how hidden states evolve over time and generate observations, supporting both probabilistic system identification and neural sequence learning. Approaches range from Kalman filtering, smoothing, and particle or variational inference to structured S4/HiPPO models, selective Mamba scans, and hybrids that combine recurrence with attention. They are applied to long-context language and video, time-series forecasting, and signals such as EEG, with evaluation spanning retrieval and sequence benchmarks as well as real-world prediction tasks. Their recurrent structure can offer linear-time processing and bounded memory, but efficient computation does not guarantee reliable long-range retrieval or state tracking, and practical speed, robustness, and accuracy remain important trade-offs.

Latest papers

299 papers30 papers in the last four weeks, down 12% on the four weeks before. 0.2% of all new papers.

UnMixMamba: Unmixing Guided State Space Subpixel Mapping of Crops from MODIS Time Series
Oct 28, 2026Motasem Alkayid, Yimin Zhu, Naser El-Sheimy +1Agricultural Remote Sensing Spectral Unmixing
Department of Geomatics Engineering, University of Calgary, Canada · Department of Geography, Faculty of Arts, The University of Jordan, Amman, Jordan
Autonomous Structural Discovery Of Bioprocess Dynamics And Kinetics Via LLM-Driven Agents
Oct 26, 2026Erdal Aydin, Yaman ArkunState Space Models Large Language Model-Guided Scientific Discovery
School of Chemical Engineering, Aalto University, Espoo 02150, Finland · Department of Chemical and Biological Engineering, Koc University, 34450, Istanbul, Türkiye
Real-Time Human Trajectory Prediction from RGB-D for Mobile Robots Using Bi-Mamba
Oct 24, 2026Basheer Al-Tawil, Magnus Jung, Ayoub Al-HamadiHuman Trajectory Prediction State Space Models
Neuro Information Technology, Otto von Guericke University, 39106 Magdeburg, Germany
A Gaussian Process State Space Formulation for Materials Constitutive Modeling: Application to Quasi-brittle Materials
Oct 23, 2026Houlin Xu, Chenyang Li, K. T. Ramesh +1State Space Models Materials Science
Hopkins Extreme Materials Institute, Johns Hopkins University, Baltimore, MD, USA · Department of Mechanical Engineering, Johns Hopkins University, Baltimore, MD, USA · Department of Civil and Systems Engineering, Johns Hopkins University, Baltimore, MD, USA
SSMCGM-Stream: A Streaming State-Space Model for Personalized Diabetes Management
Oct 20, 2026Shakson Isaac, Chirag PatelBlood Glucose Forecasting Explainable Time Series Forecasting
Department of Biomedical Informatics, Harvard Medical School
Understanding the Inner Workings of a State-Space Foundation Model for Limit Order Books
Oct 20, 2026Valentin Mohl, Alexandre Bismuth, Aramis Marti-Shahandeh +6Limit Order Book Modeling State Representation Learning
British Open-ended Learning and Discovery Lab (BOLD), Department of Computer Science, University of Oxford, Oxford, United Kingdom · Harvard University, Cambridge, MA, United States · British Open-ended Learning and Discovery Lab (BOLD), Department of Engineering Science, University of Oxford, Oxford, United Kingdom +3
GraphCast-Mamba: Learning Non-Markovian Corrections for Weather Forecasting
Oct 20, 2026Ilya Vilkoviskiy, Liang-Hong Mo, Suozhi Huang +1Weather Forecasting Time Series Forecasting
Department of Physics, Princeton University, Princeton, NJ 08544, USA · Department of Electrical and Computer Engineering, Princeton University, Princeton, NJ 08544, USA · École Polytechnique Fédérale de Lausanne (EPFL), 1015 Lausanne, Switzerland +2
Model- and Layer-Level Closed-Loop Forecasting with SSM-Based Spiking Neural Networks
Oct 20, 2026Erik Stolt, Sanja Karilanova, Ayca OzcelikkaleTime Series Forecasting Spiking Neural Networks
Department of Electrical Engineering, Uppsala University, Uppsala, Sweden
Causal Spatiotemporal State Evolution for Monocular 4D Reconstruction
Oct 20, 2026Qiaowei Miao, Yijing Guo, Lipei Zhang +44D Reconstruction Dynamic Scene Reconstruction
Zhejiang University · ShanghaiTech University · University of Cambridge +2
GTSM: Gaussian Splatting with Thermal State-Space Dynamics for Spatio-Temporal Thermal Field Reconstruction and Prediction
Oct 17, 2026Yunpeng Zhao, Haoxiang Zhang, Chao LiuSpatiotemporal Forecasting Thermal Imaging
Key Laboratory for Information Science of Electromagnetic Waves (MoE), Fudan University, Shanghai 200433, China · Department of Electronic Engineering, Tsinghua University, Beijing, China
Rethinking EEG Spatial Super-Resolution as Dynamic State Decomposition and Filtering
Oct 17, 2026Hongjun Liu, Leyu Zhou, Chang Ge +2Electroencephalography State Space Models
University of Science and Technology Beijing
AeroChem: Closed-loop Physics-Informed State Space Modeling for Long-term Chemically-Reactive Air Quality Forecasting--Extended Version
Oct 12, 2026Kien Le Trung, Tung Kieu, Dinh Duc Nha Nguyen +3Air Quality Prediction Long-Term Time Series Forecasting
VinUniversity Vietnam · Aalborg University Denmark · CECS, VinUniversity Vietnam +2
When Dynamic Scaling Fails: A Scale-State Feedback Governs Recurrent-State Quantization in Linear-Attention and SSM LLMs
Oct 10, 2026Yuhang JiangRecurrent-State Quantization LLM Quantization
Independent Researcher
ReplaySSM: Cache SSM Inputs, Not State
Oct 9, 2026Ze-Wei Liou, Harris Nover, Amey Naik +4Inference Acceleration LLM Inference Acceleration
Princeton University · NVIDIA
READ: Reading the Selective Scan for Faithful Video Attribution
Oct 9, 2026Magdalena Trędowicz, Piotr Kubaty, Arkadiusz Lewicki +2Feature Attribution Selective SSMs
Jagiellonian University, Kraków, Poland · University of Information Technology and Management in Rzeszów, Poland
Scan-Parallel Variational Inference for event-driven Latent Jump Models
Oct 9, 2026Vansh Bansal, Min Chen, James G. ScottState Space Models Irregular Time-Series Modeling
Department of Statistics and Data Science UT Austin
Time Delay System for Sequence Modeling
Oct 9, 2026Youshan Zhang, Jialu LiSequence Modeling Temporal Attention
School of Artificial Intelligence, Chuzhou University, Chuzhou, China · Department of Electrical and Computer Engineering, Boston University, Boston, USA
SpikeSSL: A Universal Spike Inference Framework with Dynamics-Informed State-Space Layers
Oct 8, 2026Chenghao Yue, Siming Xing, Shuran Liu +2Neural Decoding State Space Models
School of Life Sciences, Tsinghua University, Beijing, China · School of Future Information Innovation, Fudan University, Shanghai, China
Lyapunov-Inspired LyRIC Activation and GLARE Attention in Chaos-Guided State Space Modeling for EMG-To-Speech (ETS) Synthesis
Oct 6, 2026Sajid Fardin Dipto, Tarikul Islam Tamiti, Luke Baja-Ricketts +2State Space Models Chaotic Dynamical Systems
Department of Cyber Security Engineering George Mason University Fairfax, VA, USA
MaRK: Markov-adapted Recurrent Kernels for Dynamic Operator Conditioning in State Space Models
Oct 6, 2026Syed Ibrahim Omer, Ginny Y. Wong, Xiangyu ZhaoState Space Models Diffusion Model Fine-Tuning
Department of Data Science, City University of Hong Kong · NVIDIA AI Technology Center, NVIDIA, Santa Clara, USA
WaveGSSM: Graph Wave State Space Models for Propagating Spatio-Temporal Patterns
Oct 5, 2026Junyou Zhu, Fenying Cai, Ping Xiong +5Spatiotemporal Forecasting State Space Models
Potsdam Institute for Climate Impact Research, Germany · Machine Learning Group, Technical University of Berlin, Germany · Department of Computer Science, University of Illinois at Chicago, USA +2
S $^3$ N: A Spherical Spiral Scanning Network for Weather Forecasting
Oct 3, 2026Fan Yan, Chen Hui, Weisi Lin +4Weather Forecasting Spatiotemporal Forecasting
Nanjing University of Information Science and Technology · Nanyang Technological University · Harbin Institute of Technology +2
Bounded Reachability & Jailbreak Detection via Contraction-Constrained State Space Models
Oct 2, 2026Omanshu ThapliyalCertified Robustness State Space Models
Strategic Data Solutions Lab, Hitachi America Ltd. Santa Clara, CA 94086, USA
A Structured State Space Sequence Model for Multi-Class Classification of Malware
Oct 1, 2026Emmanuela Andam, Rana Shaaban, Emanuel Grant +1Cybersecurity Malware Classification
Artificial Intelligence Research (AIR) Center · School of Electrical Engineering and Computer Science, College of Engineering & Mines University of North Dakota, Grand Forks, ND 58201, USA
Action-On-Item Preference Flow: A Shared Event Schema for Predictive and Generative Personalization
Oct 1, 2026Parthiv Chatterjee, Kashish Kanjaria, Vashisth Purani +2User Modeling State Tracking
KDM Lab, Dhirubhai Ambani University · Dhirubhai Ambani University · LCS2 Lab, Indian Institute of Technology Delhi
State-Space Unlearning for Non-Stationary Bias in Land Surface Forecasting
Sep 30, 2026Anidipta PalMachine Unlearning State Space Models
Heritage Institute of Technology, Kolkata, India
CAMOS: Coupled Oscillatory State-Space Model for Multimodal Clinical Time-Series
Sep 30, 2026Maxx Richard Rahman, Mostafa Hammouda, Wolfgang MaassIrregular Time-Series Modeling Missing-Modality Learning
Saarland University and German Research Center for Artificial Intelligence (DFKI) Saarbrücken, Germany · Saarland University Saarbrücken, Germany
SCORE-LM: State-Space Radar Representations with Language Models for Fault Diagnosis
Sep 30, 2026Mainak Mallick, Seung-Kyum ChoiFault Detection Fault Diagnosis
Georgia Institute of Technology, Atlanta, GA, USA
Non-Commutative Lie-Algebraic State-Space Models: Finite-Division Variety Laws, Semidirect Cascades, and Gradient Saddle Escape
Sep 29, 2026Zeyu JiaState Space Models Sequence Modeling
School of Biomedical Engineering and Technology, Tianjin Medical University, Medical School, Tianjin University · School of Biomedical Engineering and Technology, Tianjin Medical University · Medical School, Tianjin University
Fractional State Space Transition for Long Sequence Modeling
Sep 28, 2026Ivan Kobyzev, Abbas Ghaddar, Ali Nasiri-Sarvi +2State Space Language Models State Space Models
Huawei Noah’s Ark Lab, Montreal Research Center, Canada

Oct 28, 2026J/K move · Enter open · S save

UnMixMamba: Unmixing Guided State Space Subpixel Mapping of Crops from MODIS Time Series

Motasem Alkayid, Yimin Zhu, Naser El-Sheimy, Lincoln Linlin Xu

Department of Geomatics Engineering, University of Calgary, Canada · Department of Geography, Faculty of Arts, The University of Jordan, Amman, Jordan

Agricultural Remote Sensing Spectral Unmixing Remote Sensing Image Super-Resolution State Space Models

Open paper AskPDF arXiv

Subpixel mapping (SPM) of crop types from \SI{250}{m} Moderate Resolution Imaging Spectroradiometer (MODIS) time series to field-scale Agriculture and Agri-Food Canada (AAFC) labels supports acreage estimation and agricultural monitoring. Three difficulties remain: (i)spectral-temporal coupling and mixed pixels that break direct coarse-to-fine classifiers; (ii)intra-class endmember variability that a single spectrum per crop cannot capture; and (iii)uniform refinement on the high-resolution (HR) grid, which treats every subpixel the same, so most of the effort goes to easy pixels while errors remain in the minority class. UnMixMamba addresses them as follows. For(i), a temporal-spectral-spatial decoupled (TSSD) factorization estimates simplex fractions and drives AAFC classification from the same mixture field, instead of mapping low-resolution (LR) observations directly to HR logits. For(ii), $\times 8$ abundance super-resolution and a learnable per-crop variant endmember bank reconstruct the MODIS cube at LR and HR under a linear mixing model. For(iii), the predicted crop fractions decide where a fixed Mamba token budget is spent, so HR refinement focuses on the minority class instead of the full grid. On Alberta 2015 under a fixed spatial-block protocol, UnMixMamba reaches OA 0.8397, mIoU 0.6640, AA 0.7837, and Kappa 0.7715, ahead of ST-DRes, ESPCN, FineCrop, AgriFM, and classical SPM baselines. The task is closed-set four-crop mapping inside a known agricultural mask.