State Space Models

Also known as SSM

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28 papers in the last four weeks, up 250% on the four weeks before. 0.3% of all new papers.

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Long-Context Modeling via GSS-Transformer Hybrid Architecture with Learnable Mixing
Jun 15, 2026Kuzey Torlak, Hüseyin Arda Arslan, Anıl Dervişoğlu +2Long-Context Language Modeling State Space Models
Kadıköy Anadolu High School · Politecnico di Torino · Istanbul Technical University +2
Nonlocal Bayesian Modeling of Continuous Spatio-Temporal Dynamics
Jun 12, 2026Jaeyeong Lee, Heeyoung KimIrregular Time-Series Modeling Bayesian Inference
Department of Industrial and Systems Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea
Structured Noise Adaptation for Sequential Bayesian Filtering with Embedded Latent Transfer Operators
Jun 12, 2026Naichang Ke, Pongpisit Thanasutives, Yoshinobu KawaharaKalman Filtering Bayesian Filtering
The University of Osaka · RIKEN Center for Advanced Intelligence Project (AIP)
LongSpike: Fractional Order Spiking State Space Models for Efficient Long Sequence Learning
Jun 11, 2026Xinrui He, Qiyu Kang, Xuhao Li +1Long-Context Modeling Spiking Neural Networks
Wuhan University · University of Science and Technology of China · Anhui University
Lung-SRAD: Spectral-Aware Regularized Audio DASS with Dual-Axis Patch-Mix Contrastive Learning for Respiratory Sound Classification
Jun 10, 2026Hemansh Shridhar, Miika Toikkanen, June-Woo KimContrastive Learning Spectral Regularization
RSC LAB, MODULABS, Republic of Korea · Department of Electronic Engineering, Wonkwang University, Republic of Korea · AI Convergence Research Institute, Wonkwang University, Republic of Korea
Nonlinear Bayesian Estimator for Parameter Learning: A Fixed-Point Characterization
Jun 8, 2026Sasan Vakili, Daniël Woonings, Pradyumna Paruchuri +1Parameter Estimation Bayesian Inference
Delft University of Technology, The Netherlands · University of Toronto, Canada
Graph Mamba Operator: A Latent Simulator for Interacting Particle Systems
Jun 8, 2026Karn Tiwari, Niladri Dutta, N M Anoop Krishnan +1Latent Dynamics Modeling Spatiotemporal GNNs
Department of Electrical Communication Engineering Indian Institute of Science, Bangalore Bengaluru, 560012, India · Department of Computer Science and Automation Indian Institute of Science, Bangalore Bengaluru, 560012, India · Yardi School of Artificial Intelligence Indian Institute of Technology, Delhi New Delhi, 110016, India
Generalizing Geometry-Guided Mamba as a Plug-and-Play Context Module for CNN-based Semantic Segmentation
Jun 7, 2026Hsin-Jui Pan, Sheng-Wei Chan, Chun-Po Shen +1Mamba Semantic Segmentation
Department of Electrical and Computer Engineering, Tamkang University, New Taipei City, Taiwan
DeepMine-Mamba: Mitigating Information Dilution in Mamba-Based State Space Models for Document Image Binarization
Jun 7, 2026Sheng-Wei Chan, Yung-Che Wang, Hsin-Jui Pan +2Mamba Document Image Understanding
Department of Electrical and Computer Engineering, Tamkang University, No.151, Yingzhuan Rd., Tamsui Dist., New Taipei City, 251301, Taiwan
HoT-SSM:Higher-order Temporal Knowledge Graph Reasoning with State Space Models for Health Care
Jun 4, 2026Thummaluru Siddartha Reddy, Vempalli Naga Sai Saketh, Yash Punjabi +1Clinical Outcome Prediction Hypergraph Neural Networks
Fujitsu Research of India, Bangalore
Learning Control-Affine Reduced-Order Models via Autoencoders
Jun 3, 2026Ali Mjalled, Martin MönnigmannNonlinear System Identification System Identification
Automatic Control and Systems Theory Ruhr-Universität Bochum Universitätstraße 150, 44801, Bochum
Learning Long Range Spatio-Temporal Representations over Continuous Time Dynamic Graphs with State Space Models
Jun 3, 2026Ayushman Raghuvanshi, Thummaluru Siddartha Reddy, Sundeep Prabhakar Chepuri +1Long-Context Modeling Temporal Link Prediction
Department of Electrical Communication Engineering, Indian Institute of Science, Bangalore
Forget Attention: Importance-Aware Attention Is All You Need
Jun 1, 2026Suhyeong Shin, Yeongwook YangSoftmax Attention Long-Context Language Modeling
Department of Computer Engineering Kangwon National University
Physics-Guided Recurrent State-Space Neural Networks for Multi-Step Prediction
Jun 1, 2026Ruiyuan Li, Ajay Seth, Manon KokTime Series Forecasting Recurrent Neural Networks
Delft Center for Systems and Control, TU Delft, the Netherlands · Department of Biomechanical Engineering, TU Delft, the Netherlands
State-Coupled Volatility in Latent Dynamical Systems: Recovery Under Partial Observation
Jun 1, 2026Imani BeckettParticle Filtering Latent Dynamics Modeling
The Herbert Wertheim School of Public Health and Human Longevity Science University of California San Diego
Computation-Aware Kalman Filtering with Model Selection for Neural Dynamics
May 31, 2026JR Huml, Jonathan Wenger, John P. CunninghamDynamical Systems Bayesian Filtering
Department of Statistics, Columbia University; Zyphra Technologies · Department of Statistics, Columbia University; Zuckerman Institute
Harmonic: Hierarchical State Space Models for Efficient Long-Context Language Modeling
May 30, 2026Petr NyomaLong-Context Language Modeling State Space Models
Independent Researcher
3D Segment Anything Model with Visual Mamba for Diagnosing Placenta Accreta Spectrum
May 30, 2026Yuliang Zhang, Fang He, Lulu Peng +5Promptable Image Segmentation Medical Diagnosis
Department of Obstetrics and Gynecology, The Third Affiliated Hospital, Guangzhou Medical University, Guangzhou 510000, China · Department of Obstetrics, Guangzhou Women and Children’s Medical Center, Guangzhou Medical University, Guangzhou 510180, China · Department of Radiology, The Third Affiliated Hospital, Guangzhou Medical University, Guangzhou 510000, China +1
Oscillatory State-Space Models as Inductive Biases for Physics-Informed Neural PDE Solvers
May 29, 2026Abhishek Chandra, Taniya KapoorNeural PDE Solvers Physics-Informed ML
KTH Royal Institute of Technology Stockholm, Sweden · Wageningen University & Research Wageningen, The Netherlands
BiSegMamba: Efficient Bidirectional Tri-Oriented Mamba for 3D Medical Image Segmentation
May 29, 2026Bakht Zada, Chao Tong, Qile Su +13D Medical Image Segmentation State Space Models
School of Computer Science and Engineering, Beihang University. State Key Laboratory of Virtual Reality Technology and Systems, Beihang University
CaMBRAIN: Real-time, Continuous EEG Inference with Causal State Space Models
May 27, 2026Abhilash Durgam, Nyle Siddiqui, Jeffrey A. Chan-Santiago +3Efficient Neural Network Inference Electroencephalography
CRCV, University of Central Florida · Department of MAE, University of Central Florida · Department of Neurology, Loma Linda University
DinoComplete: 3D Shape Completion with Distilled Semantic Priors and State Space Models
May 26, 2026Furkan Mert Algan, Eckehard Steinbach3D Reconstruction 3D Shape Completion
Chair of Media Technology · Munich Institute of Robotics and Machine Intelligence · School of Computation Information and Technology, Technical University of Munich
Interdomain Attention: Beyond Token-Level Key-Value Memory
May 23, 2026Naoki Kiyohara, Harrison Bo Hua Zhu, Riccardo El Hassanin +4Self-Attention Long-Context Language Modeling
TGSD: Topology-Guided State-Space Diffusion Framework for EEG Spatial Super-Resolution
May 22, 2026Zijian Kang, Weiming Zeng, Yueyang Li +4Electroencephalography Conditional Diffusion Models
Lab of Digital Image and Intelligent Computation, Shanghai Maritime University, Shanghai 201306, China · Department of Department of Language Science and Technology, The Hong Kong Polytechnic University, Hong Kong SAR, China · Affiliated Lianyungang Hospital of Xuzhou Medical University, Lianyungang 222002, China
Truncated Neural Likelihood Estimation for Simulation-Based Inference in State-Space Models
May 20, 2026Kostas Tsampourakis, Víctor ElviraSimulation-Based Inference Parameter Estimation
School of Mathematics, University of Edinburgh,, EH9 3FD, U.K.
Deformba: Vision State Space Model with Adaptive State Fusion
May 20, 2026Hongyu Ke, Jack Morris, Yongkang Liu +4Visual SSMs State Space Models
Department of Computer Science, Georgia State University · University of Tennessee Knoxville · InfoTech Labs, Toyota Motor North America R&D.
Efficient Learning of Deep State Space Models via Importance Smoothing
May 20, 2026John-Joseph Brady, Nikolas Nusken, Yunpeng LiVariational Inference State Space Models
Centre for Oral, Clinical and Translational Sciences, King’s College London, London, United Kingdom · Department of Mathematics, King’s College London, London, United Kingdom
CogScale: Scalable Benchmark for Sequence Processing
May 19, 2026Yannis Bendi-Ouis, Romain de Coudenhove, Xavier HinautRecurrent Neural Networks Synthetic Benchmark Generation
Mnemosyne · Mnemosyne Inria Bordeaux, France · ENS-PSL +1
Flash PD-SSM: Memory-Optimized Structured Sparse State-Space Models
May 18, 2026Aleksandar Terzić, Francesco Carzaniga, Nicolas Menet +4Efficient Language Model Inference Sequence Modeling
1IBM Research – Zurich · Department of Computer Science, ETH Zürich · *Research conducted at IBM Research – Zurich.
Mamba-VGGT: Persistent Long-Sequence Video Geometry Grounded Transformer via External Sliding Window Mamba Memory
May 17, 2026Tianchen Deng, Zhenxiang Xiong, Nailin Wang +43D ViTs 3D Reconstruction
Shanghai Jiao Tong University · Nanyang Technological University · ETH Zurich +1

Jun 15, 2026, cs.CLJ/K move · Enter open · S save

Long-Context Modeling via GSS-Transformer Hybrid Architecture with Learnable Mixing

Kuzey Torlak, Hüseyin Arda Arslan, Anıl Dervişoğlu, Beyza Nur Deniz+1

Kadıköy Anadolu High School · Politecnico di Torino · Istanbul Technical University+2

Long-Context Language Modeling State Space Models

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Modeling long-range dependencies remains a central challenge in natural language processing. Transformer architectures achieve strong performance via self-attention but scale quadratically (

O(N^2)

) with sequence length, while State Space Models (SSMs) scale linearly (

O(N)

) but suffer from a selective recall bottleneck, struggling to retrieve precise information from compressed states. This creates a fundamental tradeoff between efficiency and perplexity. To tackle these challenges, we propose the \textit{Parallel Hybrid Architecture (PHA)}, which runs Gated State Spaces (GSS), Grouped Query Attention (GQA), and Feed-Forward Networks (FFNs) as independent parallel branches fused by a learnable mixing mechanism. Instead of forcing SSMs to approximate attention or serializing the two paradigms, PHA allows each branch to specialize: GSS captures global context, while attention performs selective retrieval, with FFN providing complementary processing. On WikiText-103, PHA achieves 16.51 PPL at 125M parameters, outperforming Hedgehog (16.70) and H3-125M (23.70). Scaling to 180M parameters yields 16.42 PPL, which gives comparable results with the pure attention baseline while delivering 24% higher throughput and up to 40% lower memory usage at long contexts. On OpenWebText, our 125M model achieves 19.72 PPL, outperforming standard Transformers (20.60) and GSS hybrid baselines (19.80). These results demonstrate that separating sequence modeling paradigms into parallel specialists enables Transformer-level perplexity with substantially improved efficiency for long-context language modeling.

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Latest papers 181