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https://github.com/yyyujintang/Awesome-Mamba-Papers
Awesome Papers related to Mamba.
https://github.com/yyyujintang/Awesome-Mamba-Papers
List: Awesome-Mamba-Papers
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Awesome Papers related to Mamba.
- Host: GitHub
- URL: https://github.com/yyyujintang/Awesome-Mamba-Papers
- Owner: yyyujintang
- Created: 2024-01-28T11:21:33.000Z (11 months ago)
- Default Branch: main
- Last Pushed: 2024-10-17T14:58:55.000Z (about 2 months ago)
- Last Synced: 2024-10-25T21:53:01.783Z (about 2 months ago)
- Size: 166 KB
- Stars: 1,160
- Watchers: 28
- Forks: 60
- Open Issues: 7
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Metadata Files:
- Readme: README.md
Awesome Lists containing this project
- Awesome-Mamba-Collection - [URL
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README
# Awesome-Mamba-Papers
 
This repository compiles a list of papers related to Mamba and SSM.
Continual improvements are being made to this repository. If you come across any relevant papers that should be included, please don't hesitate to open an issue.
## News
- SegMamba accepted by MICCAI24!
- Mamba-2, VIM, Caduceus accepted by ICML24!
## Survey
(Arxiv 24.04.15) State Space Model for New-Generation Network Alternative to Transformers: A Survey [Paper](https://arxiv.org/abs/2404.09516) [Code](https://github.com/Event-AHU/Mamba_State_Space_Model_Paper_List) 
(Arxiv 24.04.24) A Survey on Visual Mamba [Paper](https://arxiv.org/abs/2404.15956)
(Arxiv 24.04.24) Mamba-360: Survey of State Space Models as Transformer Alternative for Long Sequence Modelling: Methods, Applications, and Challenges [Paper](https://arxiv.org/abs/2404.16112) [Code](https://github.com/badripatro/mamba360) 
(Arxiv 24.04.29) A Survey on Vision Mamba: Models, Applications and Challenges [Paper](https://arxiv.org/abs/2404.18861) [Code](https://github.com/Ruixxxx/Awesome-Vision-Mamba-Models) 
(Arxiv 24.05.07) Vision Mamba: A Comprehensive Survey and Taxonomy [Paper](https://arxiv.org/abs/2405.04404) [Code](https://github.com/lx6c78/Vision-Mamba-A-Comprehensive-Survey-and-Taxonomy) 
(Arxiv 24.06.05) Computation-Efficient Era: A Comprehensive Survey of State Space Models in Medical Image Analysis [Paper](https://arxiv.org/abs/2406.03430) [Code](https://github.com/xmindflow/Awesome_Mamba) 
## State Space Model (SSM)
(NeurIPS 2020 Spotlight) HiPPO: Recurrent Memory with Optimal Polynomial Projections [Paper](https://arxiv.org/abs/2008.07669) [Code](https://github.com/HazyResearch/hippo-code) 
(ICLR 2022) S4: Efficiently Modeling Long Sequences with Structured State Spaces [Paper](https://arxiv.org/abs/2111.00396v3) [Code ](https://github.com/state-spaces/s4)
(ICLR 2023) H3: Hungry Hungry Hippos: Toward Language Modeling with State Space Models [Paper](https://arxiv.org/abs/2212.14052) [Code](https://github.com/HazyResearch/H3) 
(Arxiv 24.05.26) A Unified Implicit Attention Formulation for Gated-Linear Recurrent Sequence Models [Paper](https://arxiv.org/abs/2405.16504) [Code](https://github.com/Itamarzimm/UnifiedImplicitAttnRepr) 
(Arxiv 24.05.27) The Expressive Capacity of State Space Models: A Formal Language Perspective [Paper](https://arxiv.org/abs/2405.17394) [Code](https://github.com/LeapLabTHU/MLLA) 
**(Arxiv 24.05.31, ICML24, Mamba-2) Transformers are SSMs: Generalized Models and Efficient Algorithms Through Structured State Space Duality** [Paper](https://arxiv.org/abs/2405.21060) [Code](https://github.com/state-spaces/mamba) 
**(Arxiv 24.06.04) GrootVL: Tree Topology is All You Need in State Space Model** [Paper](https://arxiv.org/abs/2406.02395) [Code](https://github.com/EasonXiao-888/GrootVL) 
**(Arxiv 24.06.12) An Empirical Study of Mamba-based Language Models** [Paper](https://arxiv.org/abs/2406.07887)
## Mamba
**(Arxiv 23.12.01) Mamba: Linear-Time Sequence Modeling with Selective State Spaces** [Paper](https://arxiv.org/abs/2312.00752) [Code](https://github.com/state-spaces/mamba) 
(Arxiv 24.01.08) MoE-Mamba: Efficient Selective State Space Models with Mixture of Experts [Paper](https://arxiv.org/abs/2401.04081)
(Arxiv 24.01.24) MambaByte: Token-free Selective State Space Model [Paper](https://arxiv.org/abs/2401.13660) [Code](https://github.com/lucidrains/MEGABYTE-pytorch) 
(Arxiv 24.01.31) LOCOST: State-Space Models for Long Document Abstractive Summarization [Paper](https://arxiv.org/abs/2401.17919) [Code](https://github.com/flbbb/locost-summarization) 
(Arxiv 24.02.01) BlackMamba: Mixture of Experts for State-Space Models [Paper](https://arxiv.org/abs/2402.01771) [Code](https://github.com/Zyphra/BlackMamba) 
(Arxiv 24.02.06) Can Mamba Learn How to Learn? A Comparative Study on In-Context Learning Tasks [Paper](https://arxiv.org/abs/2402.04248)
(Arxiv 24.02.08) Mamba-ND: Selective State Space Modeling for Multi-Dimensional Data [Paper](https://arxiv.org/abs/2402.05892)
(Arxiv 24.02.15) Hierarchical State Space Models for Continuous Sequence-to-Sequence Modeling [Paper](https://arxiv.org/abs/2402.10211) [Code](https://github.com/raunaqbhirangi/hiss) 
(Arxiv 24.02.19) Pan-Mamba: Effective pan-sharpening with State Space Model [Paper](https://arxiv.org/abs/2402.12192) [Code](https://github.com/alexhe101/Pan-Mamba) 
(**CVPR24**) State Space Models for Event Cameras [Paper](https://arxiv.org/abs/2402.15584) [Code](https://github.com/uzh-rpg/ssms_event_cameras) 
(Arxiv 24.02.26) DenseMamba: State Space Models with Dense Hidden Connection for Efficient Large Language Models [Paper](https://arxiv.org/abs/2403.00818) [Code ](https://github.com/WailordHe/DenseSSM)
(Arxiv 24.03.03) The Hidden Attention of Mamba Models [Paper](https://arxiv.org/abs/2403.01590) [Code ](https://github.com/AmeenAli/HiddenMambaAttn)
(Arxiv 24.03.08) MamMIL: Multiple Instance Learning for Whole Slide Images with State Space Models [Paper](https://arxiv.org/abs/2403.05160)
(Arxiv 24.03.11) MambaMIL: Enhancing Long Sequence Modeling with Sequence Reordering in Computational Pathology [Paper](https://arxiv.org/abs/2403.06800) [Code](https://github.com/isyangshu/MambaMIL) 
(Arxiv 24.03.12) Motion Mamba: Efficient and Long Sequence Motion Generation with Hierarchical and Bidirectional Selective SSM [Paper](https://arxiv.org/abs/2403.07487) [Code](https://github.com/steve-zeyu-zhang/MotionMamba) 
(Arxiv 24.03.13) ClinicalMamba: A Generative Clinical Language Model on Longitudinal Clinical Notes [Paper](https://arxiv.org/abs/2403.05795)
(Arxiv 24.03.26) State Space Models as Foundation Models: A Control Theoretic Overview [Paper](https://arxiv.org/abs/2403.16899)
(Arxiv 24.03.28) Jamba: A Hybrid Transformer-Mamba Language Model [Paper](https://arxiv.org/abs/2403.19887) [Code](https://huggingface.co/ai21labs/Jamba-v0.1)
(Arxiv 24.03.29) HARMamba: Efficient Wearable Sensor Human Activity Recognition Based on Bidirectional Selective SSM [Paper](https://arxiv.org/abs/2403.20183)
(Arxiv 24.04.07) VMambaMorph: a Visual Mamba-based Framework with Cross-Scan Module for Deformable 3D Image Registration [Paper](https://arxiv.org/abs/2404.05105) [Code](https://github.com/ziyangwang007/VMambaMorph) 
(Arxiv 24.04.12) SpectralMamba: Efficient Mamba for Hyperspectral Image Classification [Paper](https://arxiv.org/abs/2404.08489) [Code](https://github.com/danfenghong/SpectralMamba) 
\(**Arxiv 24.05.13) MambaOut: Do We Really Need Mamba for Vision?** [Paper](https://arxiv.org/abs/2405.07992) [Code](https://github.com/yuweihao/MambaOut) 
(Arxiv 24.05.19) NetMamba: Efficient Network Traffic Classification via Pre-training Unidirectional Mamba [Paper](https://arxiv.org/abs/2405.11449)
(Arxiv 24.05.23) EHRMamba: Towards Generalizable and Scalable Foundation Models for Electronic Health Records [Paper](https://arxiv.org/abs/2405.14567)
(Arxiv 24.05.26) Mamba4KT:An Efficient and Effective Mamba-based Knowledge Tracing Model [Paper](https://arxiv.org/abs/2405.16542)
(Arxiv 24.05.26) Zamba: A Compact 7B SSM Hybrid Model [Paper](https://arxiv.org/abs/2405.16712)
(Arxiv 24.05.30) MSSC-BiMamba: Multimodal Sleep Stage Classification and Early Diagnosis of Sleep Disorders with Bidirectional Mamba [Paper](https://arxiv.org/abs/2405.20142)
## Language/Sequence Modeling
**(Arxiv 24.03.05, ICML24) Caduceus: Bi-Directional Equivariant Long-Range DNA Sequence Modeling** [Paper](https://arxiv.org/abs/2403.03234) [Code](https://github.com/kuleshov-group/caduceus) 
(Arxiv 24.06.11) Samba: Simple Hybrid State Space Models for Efficient Unlimited Context Language Modeling [Paper](https://arxiv.org/abs/2406.07522)
## Vision
**(Arxiv 24.01.17) Vision Mamba: Efficient Visual Representation Learning with Bidirectional State Space Model** [Paper](https://arxiv.org/abs/2401.09417) [Code](https://github.com/hustvl/Vim) 
**(Arxiv 24.01.18) VMamba: Visual State Space Model** [Paper](https://arxiv.org/abs/2401.10166) [Code](https://github.com/MzeroMiko/VMamba) 
(Arxiv 24.02.05) Swin-UMamba: Mamba-based UNet with ImageNet-based pretraining [Paper](https://arxiv.org/abs/2402.03302) [Code](https://github.com/JiarunLiu/Swin-UMamba) 
(Arxiv 24.02.06) U-shaped Vision Mamba for Single Image Dehazing [Paper](https://arxiv.org/abs/2402.04139) [Code](https://github.com/zzr-idam/UVM-Net) 
(Arxiv 24.02.23) MambaIR: A Simple Baseline for Image Restoration with State-Space Model [Paper](https://arxiv.org/abs/2402.15648) [Code](https://github.com/csguoh/MambaIR) 
(Arxiv 24.02.24) Res-VMamba: Fine-Grained Food Category Visual Classification Using Selective State Space Models with Deep Residual Learning [Paper](https://arxiv.org/abs/2402.15761) [Code ](https://github.com/ChiShengChen/ResVMamba)
(Arxiv 24.03.04) MiM-ISTD: Mamba-in-Mamba for Efficient Infrared Small Target Detection [Paper](https://arxiv.org/abs/2403.02148) [Code](https://github.com/txchen-USTC/MiM-ISTD) 
(Arxiv 24.03.15) EfficientVMamba: Atrous Selective Scan for Light Weight Visual Mamba [Paper](https://arxiv.org/abs/2403.09977) [Code](https://github.com/TerryPei/EfficientVMamba) 
(Arxiv 24.03.15) On the low-shot transferability of [V]-Mamba [Paper](https://arxiv.org/abs/2403.10696)
(Arxiv 24.03.26) PlainMamba: Improving Non-Hierarchical Mamba in Visual Recognition [Paper](https://arxiv.org/abs/2403.17695) [Code](https://github.com/ChenhongyiYang/PlainMamba) 
(Arxiv 24.03.26) Integrating Mamba Sequence Model and Hierarchical Upsampling Network for Accurate Semantic Segmentation of Multiple Sclerosis Legion [Paper](https://arxiv.org/abs/2403.17432)
(Arxiv 24.03.27) Gamba: Marry Gaussian Splatting with Mamba for single view 3D reconstruction [Paper](https://arxiv.org/abs/2403.18795)
(Arxiv 24.03.27) ReMamber: Referring Image Segmentation with Mamba Twister [Paper](https://arxiv.org/abs/2403.17839)
(Arxiv 24.03.28) RSMamba: Remote Sensing Image Classification with State Space Model [Paper](https://arxiv.org/abs/2403.19654) [Code](https://github.com/KyanChen/RSMamba) 
(Arxiv 24.04.02) Samba: Semantic Segmentation of Remotely Sensed Images with State Space Model [Paper](https://arxiv.org/abs/2404.01705) [Code](https://github.com/zhuqinfeng1999/Samba) 
(Arxiv 24.04.03) RS3Mamba: Visual State Space Model for Remote Sensing Images Semantic Segmentation [Paper](https://arxiv.org/abs/2404.02457) [Code](https://github.com/sstary/SSRS) 
(Arxiv 24.04.03) RS-Mamba for Large Remote Sensing Image Dense Prediction [Paper](https://arxiv.org/abs/2404.02668) [Code](https://github.com/walking-shadow/Official_Remote_Sensing_Mamba) 
\(Arxiv 24.04.04) ChangeMamba: Remote Sensing Change Detection with Spatio-Temporal State Space Model [Paper](https://arxiv.org/abs/2404.03425) [Code](https://github.com/ChenHongruixuan/MambaCD) 
\(Arxiv 24.04.05) Sigma: Siamese Mamba Network for Multi-Modal Semantic Segmentation [Paper](https://arxiv.org/abs/2404.04256) [Code](https://github.com/zifuwan/Sigma) 
\(Arxiv 24.04.09) MambaAD: Exploring State Space Models for Multi-class Unsupervised Anomaly Detection [Paper](https://arxiv.org/abs/2404.06564) [Code](https://github.com/lewandofskee/MambaAD) 
\(Arxiv 24.04.15) FreqMamba: Viewing Mamba from a Frequency Perspective for Image Deraining [Paper](https://arxiv.org/abs/2404.09476)
\(Arxiv 24.04.16) Exploring Learning-based Motion Models in Multi-Object Tracking [Paper](https://arxiv.org/abs/2403.10826)
\(Arxiv 24.04.17) CU-Mamba: Selective State Space Models with Channel Learning for Image Restoration [Paper](https://arxiv.org/abs/2404.11778)
\(Arxiv 24.04.17) Text-controlled Motion Mamba: Text-Instructed Temporal Grounding of Human Motion [Paper](https://arxiv.org/abs/2404.11375)
\(Arxiv 24.04.20) Vim4Path: Self-Supervised Vision Mamba for Histopathology Images [Paper](https://arxiv.org/abs/2404.13222) [Code](https://github.com/AtlasAnalyticsLab/Vim4Path) 
\(Arxiv 24.04.28) Mamba-FETrack: Frame-Event Tracking via State Space Model [Paper](https://arxiv.org/abs/2404.18174) [Code](https://github.com/Event-AHU/Mamba_FETrack) 
\(Arxiv 24.04.28) S2Mamba: A Spatial-spectral State Space Model for Hyperspectral Image Classification [Paper](https://arxiv.org/abs/2404.18213) [Code](https://github.com/PURE-melo/S2Mamba) 
\(Arxiv 24.04.29) Spectral-Spatial Mamba for Hyperspectral Image Classification [Paper](https://arxiv.org/abs/2404.18401)
\(Arxiv 24.04.29) RSCaMa: Remote Sensing Image Change Captioning with State Space Model [Paper](https://arxiv.org/abs/2404.18895) [Code](https://github.com/Chen-Yang-Liu/RSCaMa) 
\(Arxiv 24.05.02) SOAR: Advancements in Small Body Object Detection for Aerial Imagery Using State Space Models and Programmable Gradients [Paper](https://arxiv.org/abs/2405.01726) [Code](https://github.com/yash2629/S.O.A.R) 
\(Arxiv 24.05.02) SSUMamba: Spatial-Spectral Selective State Space Model for Hyperspectral Image Denoising [Paper](https://arxiv.org/abs/2405.01828) [Code](https:/github.com/lronkitty/SSUMamba) 
\(Arxiv 24.05.05) DVMSR: Distillated Vision Mamba for Efficient Super-Resolution [Paper](https://arxiv.org/abs/2405.03008) [Code](https://github.com/nathan66666/DVMSR) 
\(Arxiv 24.05.05) AC-MAMBASEG: An adaptive convolution and Mamba-based architecture for enhanced skin lesion segmentation [Paper](https://arxiv.org/abs/2405.03011) [Code](https://github.com/vietthanh2710/AC-MambaSeg) 
\(Arxiv 24.05.06) Retinexmamba: Retinex-based Mamba for Low-light Image Enhancement [Paper](https://arxiv.org/abs/2405.03349) [Code](https://github.com/YhuoyuH/RetinexMamba) 
\(Arxiv 24.05.07) VMambaCC: A Visual State Space Model for Crowd Counting [Paper](https://arxiv.org/abs/2405.03978)
\(Arxiv 24.05.08) Frequency-Assisted Mamba for Remote Sensing Image Super-Resolution [Paper](https://arxiv.org/abs/2405.01699)
\(Arxiv 24.05.09) Rethinking Efficient and Effective Point-based Networks for Event Camera Classification and Regression: EventMamba [Paper](https://arxiv.org/abs/2405.06116)
\(Arxiv 24.05.13) GMSR:Gradient-Guided Mamba for Spectral Reconstruction from RGB Images [Paper](https://arxiv.org/abs/2405.07777)
\(Arxiv 24.05.13) OverlapMamba: Novel Shift State Space Model for LiDAR-based Place Recognition [Paper](https://arxiv.org/abs/2405.07966)
\(Arxiv 24.05.14) Rethinking Scanning Strategies with Vision Mamba in Semantic Segmentation of Remote Sensing Imagery: An Experimental Study [Paper](https://arxiv.org/abs/2405.08493)
\(Arxiv 24.05.16) IRSRMamba: Infrared Image Super-Resolution via Mamba-based Wavelet Transform Feature Modulation Model [Paper](https://arxiv.org/abs/2405.09873) [Code](https://github.com/yongsongH/IRSRMamba) 
\(Arxiv 24.05.16) RSDehamba: Lightweight Vision Mamba for Remote Sensing Satellite Image Dehazing [Paper](https://arxiv.org/abs/2405.10030)
\(Arxiv 24.05.17) CM-UNet: Hybrid CNN-Mamba UNet for Remote Sensing Image Semantic Segmentation [Paper](https://arxiv.org/abs/2405.10530) [Code](https://github.com/XiaoBuL/CM-UNet) 
\(Arxiv 24.05.16) IRSRMamba: Infrared Image Super-Resolution via Mamba-based Wavelet Transform Feature Modulation Model [Paper](https://arxiv.org/abs/2405.09873) [Code](https://github.com/yongsongH/IRSRMamba) 
\(Arxiv 24.05.20) Mamba-in-Mamba: Centralized Mamba-Cross-Scan in Tokenized Mamba Model for Hyperspectral Image Classification [Paper](https://arxiv.org/abs/2405.12003) [Code](https://github.com/zhouweilian1904/Mamba-in-Mamba) 
\(Arxiv 24.05.21) 3DSS-Mamba: 3D-Spectral-Spatial Mamba for Hyperspectral Image Classification [Paper](https://arxiv.org/abs/2405.12487)
\(Arxiv 24.05.23) Multi-Scale VMamba: Hierarchy in Hierarchy Visual State Space Model [Paper](https://arxiv.org/abs/2405.12003) [Code](https://github.com/YuHengsss/MSVMamba) 
\(Arxiv 24.05.23) Scalable Visual State Space Model with Fractal Scanning [Paper](https://arxiv.org/abs/2405.14480)
\(Arxiv 24.05.23) Mamba-R: Vision Mamba ALSO Needs Registers [Paper](https://arxiv.org/abs/2405.14858) [Code](https://github.com/wangf3014/Mamba-Reg) 
\(Arxiv 24.05.24) MUCM-Net: A Mamba Powered UCM-Net for Skin Lesion Segmentation [Paper](https://arxiv.org/abs/2405.15925)
**(Arxiv 24.05.26) Demystify Mamba in Vision: A Linear Attention Perspective** [Paper](https://arxiv.org/abs/2405.16605) [Code](https://github.com/LeapLabTHU/MLLA) 
\(Arxiv 24.05.29) Vim-F: Visual State Space Model Benefiting from Learning in the Frequency Domain [Paper](https://arxiv.org/abs/2405.18679) [Code](https://github.com/yws-wxs/Vim-F) 
\(Arxiv 24.05.29) FourierMamba: Fourier Learning Integration with State Space Models for Image Deraining [Paper](https://arxiv.org/abs/2405.19450)
\(Arxiv 24.06.06) MambaDepth: Enhancing Long-range Dependency for Self-Supervised Fine-Structured Monocular Depth Estimation [Paper](https://arxiv.org/abs/2406.04532)
\(Arxiv 24.06.09) HDMba: Hyperspectral Remote Sensing Imagery Dehazing with State Space Model [Paper](https://arxiv.org/abs/2406.05700)
\(Arxiv 24.06.09) Mamba YOLO: SSMs-Based YOLO For Object Detection [Paper](https://arxiv.org/abs/2406.05835)
\(Arxiv 24.06.09) MHS-VM: Multi-Head Scanning in Parallel Subspaces for Vision Mamba [Paper](https://arxiv.org/abs/2406.05992) [Code](https://github.com/PixDeep/MHS-VM) 
\(Arxiv 24.06.11) DualMamba: A Lightweight Spectral-Spatial Mamba-Convolution Network for Hyperspectral Image Classification [Paper](https://arxiv.org/abs/2406.07050)
\(Arxiv 24.06.11) Autoregressive Pretraining with Mamba in Vision [Paper](https://arxiv.org/abs/2406.07537) [Code](https://github.com/OliverRensu/ARM) 
## Video
(Arxiv 24.01.25) Vivim: a Video Vision Mamba for Medical Video Object Segmentation [Paper](https://arxiv.org/abs/2401.14168) [Code](https://github.com/scott-yjyang/Vivim) 
(Arxiv 24.03.11) VideoMamba: State Space Model for Efficient Video Understanding [Paper](https://arxiv.org/abs/2403.06977) [Code](https://github.com/OpenGVLab/VideoMamba) 
(Arxiv 24.04.01) SpikeMba: Multi-Modal Spiking Saliency Mamba for Temporal Video Grounding [Paper](https://arxiv.org/abs/2404.01174)
(Arxiv 24.04.09) RhythmMamba: Fast Remote Physiological Measurement with Arbitrary Length Videos [Paper](https://arxiv.org/abs/2404.06483)
(Arxiv 24.04.11) Simba: Mamba augmented U-ShiftGCN for Skeletal Action Recognition in Videos [Paper](https://arxiv.org/abs/2404.07645)
(Arxiv 24.05.05) Matten: Video Generation with Mamba-Attention [Paper](https://arxiv.org/abs/2405.03025)
(Arxiv 24.05.23) MAMBA4D: Efficient Long-Sequence Point Cloud Video Understanding with Disentangled Spatial-Temporal State Space Models [Paper](https://arxiv.org/abs/2405.14338)
(Arxiv 24.05.24) Scaling Diffusion Mamba with Bidirectional SSMs for Efficient Image and Video Generation [Paper](https://arxiv.org/abs/2405.15881)
(Arxiv 24.05.30) DeMamba: AI-Generated Video Detection on Million-Scale GenVideo Benchmark [Paper](https://arxiv.org/abs/2405.19707) [Code](https://github.com/chenhaoxing/DeMamba) 
## Spatiotemporal
(**CVPR24 Precognition Workshop**) VMRNN: Integrating Vision Mamba and LSTM for Efficient and Accurate Spatiotemporal Forecasting [Paper](https://arxiv.org/abs/2403.16536) [Code](https://github.com/yyyujintang/VMRNN-PyTorch) 
(Arxiv 24.04.20) ST-Mamba: Spatial-Temporal Selective State Space Model for Traffic Flow Prediction [Paper](https://arxiv.org/abs/2404.13257)
(Arxiv 24.04.24) ST-MambaSync: The Confluence of Mamba Structure and Spatio-Temporal Transformers for Precipitous Traffic Prediction [Paper](https://arxiv.org/abs/2404.15899)
## Medical
(Arxiv 24.01.09) U-Mamba: Enhancing Long-range Dependency for Biomedical Image Segmentation [Paper](https://arxiv.org/abs/2401.04722) [Code](https://github.com/bowang-lab/U-Mamba) 
(Arxiv 24.01.24, MICCAI24) SegMamba: Long-range Sequential Modeling Mamba For 3D Medical Image Segmentation [Paper](https://arxiv.org/abs/2401.13560) [Code](https://github.com/ge-xing/SegMamba) 
(Arxiv 24.01.25) Vivim: a Video Vision Mamba for Medical Video Object Segmentation [Paper](https://arxiv.org/abs/2401.14168) [Code](https://github.com/scott-yjyang/Vivim) 
(Arxiv 24.01.25) MambaMorph: a Mamba-based Backbone with Contrastive Feature Learning for Deformable MR-CT Registration [Paper](https://arxiv.org/abs/2401.13934) [Code](https://github.com/guo-stone/mambamorph) 
(Arxiv 24.02.04) VM-UNet: Vision Mamba UNet for Medical Image Segmentation [Paper](https://arxiv.org/abs/2402.02491) [Code](https://github.com/JCruan519/VM-UNet) 
(Arxiv 24.02.05) nnMamba: 3D Biomedical Image Segmentation, Classification and Landmark Detection with State Space Model [Paper](https://arxiv.org/abs/2402.03526) [Code ](https://github.com/lhaof/nnMamba)
(Arxiv 24.02.09) FD-Vision Mamba for Endoscopic Exposure Correction [Paper](https://arxiv.org/abs/2402.06378)
(Arxiv 24.02.16) Weak-Mamba-UNet: Visual Mamba Makes CNN and ViT Work Better for Scribble-based Medical Image Segmentation [Paper](https://arxiv.org/abs/2402.10887) [Code](https://github.com/ziyangwang007/Mamba-UNet) 
(Arxiv 24.03.06) MedMamba: Vision Mamba for Medical Image Classification [Paper](https://arxiv.org/abs/2403.03849) [Code](https://github.com/YubiaoYue/MedMamba) 
(Arxiv 24.03.08) LightM-UNet: Mamba Assists in Lightweight UNet for Medical Image Segmentation [Paper](https://arxiv.org/abs/2403.05246) [Code](https://github.com/MrBlankness/LightM-UNet) 
(Arxiv 24.03.12) Large Window-based Mamba UNet for Medical Image Segmentation: Beyond Convolution and Self-attention [Paper](https://arxiv.org/abs/2403.07332) [Code](https://github.com/wjh892521292/LMa-UNet) 
(Arxiv 24.03.20) H-vmunet: High-order Vision Mamba UNet for Medical Image Segmentation [Paper](https://arxiv.org/abs/2403.13642) [Code](https://github.com/wurenkai/H-vmunet) 
(Arxiv 24.03.20) ProMamba: Prompt-Mamba for polyp segmentation [Paper](https://arxiv.org/abs/2403.13660)
(Arxiv 24.03.25) CMViM: Contrastive Masked Vim Autoencoder for 3D Multi-modal Representation Learning for AD classification [Paper](https://arxiv.org/abs/2403.16520)
(Arxiv 24.03.26) Rotate to Scan: UNet-like Mamba with Triplet SSM Module for Medical Image Segmentation [Paper](https://arxiv.org/abs/2403.17701)
(Arxiv 24.03.29) UltraLight VM-UNet: Parallel Vision Mamba Significantly Reduces Parameters for Skin Lesion Segmentation [Paper](https://arxiv.org/abs/2403.20035) [Code](https://github.com/wurenkai/UltraLight-VM-UNet) 
(Arxiv 24.04.01) T-Mamba: Frequency-Enhanced Gated Long-Range Dependency for Tooth 3D CBCT Segmentation [Paper](https://arxiv.org/abs/2404.01065)
(MIDL 2024) ViM-UNet: Vision Mamba for Biomedical Segmentation [Paper](https://arxiv.org/abs/2404.07705) [Code](https://github.com/constantinpape/torch-em/blob/main/vimunet.md)
(Arxiv 24.05.08) HC-Mamba: Vision MAMBA with Hybrid Convolutional Techniques for Medical Image Segmentation [Paper](https://arxiv.org/abs/2405.05007)
(Arxiv 24.05.08) VM-DDPM: Vision Mamba Diffusion for Medical Image Synthesis [Paper](https://arxiv.org/abs/2405.05667)
(Arxiv 24.05.22) I2I-Mamba: Multi-modal medical image synthesis via selective state space modeling [Paper](https://arxiv.org/abs/2405.14022)
(Arxiv 24.05.25) UU-Mamba: Uncertainty-aware U-Mamba for Cardiac Image Segmentation [Paper](https://arxiv.org/abs/2405.17496)
(Arxiv 24.05.27) Enhancing Global Sensitivity and Uncertainty Quantification in Medical Image Reconstruction with Monte Carlo Arbitrary-Masked Mamba [Paper](https://arxiv.org/abs/2405.17659)
(Arxiv 24.05.28) Cardiovascular Disease Detection from Multi-View Chest X-rays with BI-Mamba [Paper](https://arxiv.org/abs/2405.18533)
(Arxiv 24.06.09) Vision Mamba: Cutting-Edge Classification of Alzheimer's Disease with 3D MRI Scans [Paper](https://arxiv.org/abs/2406.05757)
(Arxiv 24.06.09) Convolution and Attention-Free Mamba-based Cardiac Image Segmentation [Paper](https://arxiv.org/abs/2406.05786)
## Time Series
(Arxiv 24.03.14) TimeMachine: A Time Series is Worth 4 Mambas for Long-term Forecasting [Paper](https://arxiv.org/abs/2403.09898) [Code](https://github.com/Atik-Ahamed/TimeMachine) 
(Arxiv 24.03.17) Is Mamba Effective for Time Series Forecasting? [Paper](https://arxiv.org/abs/2403.11144) [Code](https://github.com/wzhwzhwzh0921/S-D-Mamba) 
(Arxiv 24.03.22) SiMBA: Simplified Mamba-Based Architecture for Vision and Multivariate Time series [Paper](https://arxiv.org/abs/2403.15360) [Code](https://github.com/badripatro/Simba) 
(Arxiv 24.04.23) Integrating Mamba and Transformer for Long-Short Range Time Series Forecasting [Paper](https://arxiv.org/abs/2404.14757) [Code](https://github.com/XiongxiaoXu/Mambaformer-in-Time-Series) 
(Arxiv 24.04.24) Bi-Mamba+: Bidirectional Mamba for Time Series Forecasting [Paper](https://arxiv.org/abs/2404.15772)
(Arxiv 24.05.11) DTMamba : Dual Twin Mamba for Time Series Forecasting [Paper](https://arxiv.org/abs/2405.07022)
(Arxiv 24.05.25) Time-SSM: Simplifying and Unifying State Space Models for Time Series Forecasting [Paper](https://arxiv.org/abs/2405.16312)
(Arxiv 24.05.26) MambaTS: Improved Selective State Space Models for Long-term Time Series Forecasting [Paper](https://arxiv.org/abs/2405.16440)
(Arxiv 24.06.06) Chimera: Effectively Modeling Multivariate Time Series with 2-Dimensional State Space Models [Paper](https://arxiv.org/abs/2406.04320)
(Arxiv 24.06.06) TSCMamba: Mamba Meets Multi-View Learning for Time Series Classification [Paper](https://arxiv.org/abs/2406.04419)
(Arxiv 24.06.08) C-Mamba: Channel Correlation Enhanced State Space Models for Multivariate Time Series Forecasting [Paper](https://arxiv.org/abs/2406.05316)
## Speech/Audio
(Arxiv 24.03.12) Multichannel Long-Term Streaming Neural Speech Enhancement for Static and Moving Speakers [Paper](https://arxiv.org/abs/2403.07675) [code](https://github.com/Audio-WestlakeU/NBSS) 
(Arxiv 24.03.27) Dual-path Mamba: Short and Long-term Bidirectional Selective Structured State Space Models for Speech Separation [Paper](https://arxiv.org/abs/2403.18257)
(Arxiv 24.04.02) SPMamba: State-space model is all you need in speech separation [Paper](https://arxiv.org/abs/2404.02063) [code](https://github.com/JusperLee/SPMamba) 
(Arxiv 24.05.02) TRAMBA: A Hybrid Transformer and Mamba Architecture for Practical Audio and Bone Conduction Speech Super Resolution and Enhancement on Mobile and Wearable Platforms [Paper](https://arxiv.org/abs/2405.01242)
(Arxiv 24.05.10) An Investigation of Incorporating Mamba for Speech Enhancement [Paper](https://arxiv.org/abs/2405.06573)
(Arxiv 24.05.18) MAMCA -- Optimal on Accuracy and Efficiency for Automatic Modulation Classification with Extended Signal Length [Paper](https://arxiv.org/abs/2405.11263) [code](https://github.com/ZhangYezhuo/MAMCA) 
(Arxiv 24.05.20) SSAMBA: Self-Supervised Audio Representation Learning with Mamba State Space Model [Paper](https://arxiv.org/abs/2405.11831) [code](https://github.com/SiavashShams/ssamba) 
(Arxiv 24.05.21) Mamba in Speech: Towards an Alternative to Self-Attention [Paper](https://arxiv.org/abs/2405.12609)
(Arxiv 24.05.22) Audio Mamba: Pretrained Audio State Space Model For Audio Tagging [Paper](https://arxiv.org/abs/2405.13636)
(Arxiv 24.06.04, INTERSPEECH 2024) Audio Mamba: Pretrained Audio State Space Model For Audio Tagging [Paper](https://arxiv.org/abs/2406.02178)
(Arxiv 24.06.05) Audio Mamba: Bidirectional State Space Model for Audio Representation Learning [Paper](https://arxiv.org/abs/2406.03344)
(Arxiv 24.06.10) RawBMamba: End-to-End Bidirectional State Space Model for Audio Deepfake Detection [Paper](https://arxiv.org/abs/2406.06086)
## Graph
(Arxiv 24.02.01) Graph-Mamba: Towards Long-Range Graph Sequence Modeling with Selective State Spaces [Paper](https://browse.arxiv.org/abs/2402.00789) [Code](https://github.com/bowang-lab/Graph-Mamba)
(Arxiv 24.02.13) Graph Mamba: Towards Learning on Graphs with State Space Models [Paper](https://arxiv.org/abs/2402.08678) [Code](https://github.com/GraphMamba/GMN) 
(Arxiv 24.03.19) STG-Mamba: Spatial-Temporal Graph Learning via Selective State Space Model [Paper](https://arxiv.org/abs/2403.12418)
(Arxiv 24.06.05) Combining Graph Neural Network and Mamba to Capture Local and Global Tissue Spatial Relationships in Whole Slide Images [Paper](https://arxiv.org/abs/2406.04377) [Code](https://github.com/rina-ding/gat-mamba) 
## Point Cloud
(Arxiv 24.02.16) PointMamba: A Simple State Space Model for Point Cloud Analysis [Paper](https://arxiv.org/abs/2402.10739) [Code](https://github.com/LMD0311/PointMamba) 
(Arxiv 24.03.01) Point Could Mamba: Point Cloud Learning via State Space Model [Paper](https://arxiv.org/abs/2403.00762) [Code ](https://github.com/zhang-tao-whu/PCM)
(Arxiv 24.04.08) 3DMambaIPF: A State Space Model for Iterative Point Cloud Filtering via Differentiable Rendering [Paper](https://arxiv.org/abs/2404.05522)
(Arxiv 24.04.10) 3DMambaComplete: Exploring Structured State Space Model for Point Cloud Completion [Paper](https://arxiv.org/abs/2404.05522)
(Arxiv 24.04.23) Mamba3D: Enhancing Local Features for 3D Point Cloud Analysis via State Space Model [Paper](https://arxiv.org/abs/2404.14966)
(Arxiv 24.05.24) PoinTramba: A Hybrid Transformer-Mamba Framework for Point Cloud Analysis [Paper](https://arxiv.org/abs/2405.15463) [Code ](https://github.com/xiaoyao3302/PoinTramba)
(Arxiv 24.06.10) PointABM:Integrating Bidirectional State Space Model with Multi-Head Self-Attention for Point Cloud Analysis [Paper](https://arxiv.org/abs/2406.06069)
## Recommendation
(Arxiv 24.03.06) Mamba4Rec: Towards Efficient Sequential Recommendation with Selective State Space Models [Paper](https://arxiv.org/abs/2403.03900) [Code](https://github.com/chengkai-liu/Mamba4Rec) 
(Arxiv 24.03.25) Uncovering Selective State Space Model's Capabilities in Lifelong Sequential Recommendation [Paper](https://arxiv.org/abs/2403.16371) [Code](https://github.com/nancheng58/RecMamba) 
(Arxiv 24.06.04) Mamba as Decision Maker: Exploring Multi-scale Sequence Modeling in Offline Reinforcement Learning [Paper](https://arxiv.org/abs/2406.02013) [Code](https://github.com/AndyCao1125/MambaDM) 
## Multimodal
(Arxiv 24.03.20) VL-Mamba: Exploring State Space Models for Multimodal Learning [Paper](https://arxiv.org/abs/2403.13600) [Code](https://github.com/ZhengYu518/VL-Mamba) 
(Arxiv 24.03.22) Cobra: Extending Mamba to Multi-Modal Large Language Model for Efficient Inference [Paper](https://arxiv.org/abs/2403.14520) [Code](https://github.com/h-zhao1997/cobra) 
(Arxiv 24.04.09) 3DMambaIPF: A State Space Model for Iterative Point Cloud Filtering via Differentiable Rendering [Paper](https://arxiv.org/abs/2404.05522)
(Arxiv 24.04.11) FusionMamba: Efficient Image Fusion with State Space Model [Paper](https://arxiv.org/abs/2404.07932)
(Arxiv 24.04.11) SurvMamba: State Space Model with Multi-grained Multi-modal Interaction for Survival Prediction [Paper](https://arxiv.org/abs/2404.08027)
(Arxiv 24.04.12) MambaDFuse: A Mamba-based Dual-phase Model for Multi-modality Image Fusion [Paper](https://arxiv.org/abs/2404.08406)
(Arxiv 24.04.14) Fusion-Mamba for Cross-modality Object Detection [Paper](https://arxiv.org/abs/2404.09146)
(Arxiv 24.04.15) FusionMamba: Dynamic Feature Enhancement for Multimodal Image Fusion with Mamba [Paper](https://arxiv.org/abs/2404.09498) [Code](https://github.com/millieXie/FusionMamba) 
(Arxiv 24.04.25) CFMW: Cross-modality Fusion Mamba for Multispectral Object Detection under Adverse Weather Conditions [Paper](https://arxiv.org/abs/2404.16302) [Code](https://github.com/lhy-zjut/CFMW) 
(Arxiv 24.04.27) Revisiting Multi-modal Emotion Learning with Broad State Space Models and Probability-guidance Fusion [Paper](https://arxiv.org/abs/2404.17858)
(Arxiv 24.04.30) CLIP-Mamba: CLIP Pretrained Mamba Models with OOD and Hessian Evaluation [Paper](https://arxiv.org/abs/2404.19394) [Code](https://github.com/raytrun/mamba-clip) 
(Arxiv 24.05.24) Meteor: Mamba-based Traversal of Rationale for Large Language and Vision Models [Paper](https://arxiv.org/abs/2405.15574) [Code](https://github.com/ByungKwanLee/Meteor) 
(Arxiv 24.05.28) Coupled Mamba: Enhanced Multi-modal Fusion with Coupled State Space Model [Paper](https://arxiv.org/abs/2405.18014)
## Reinforcement Learning
(Arxiv 24.03.29) Decision Mamba: Reinforcement Learning via Sequence Modeling with Selective State Spaces [Paper](https://arxiv.org/abs/2403.19925)
(Arxiv 24.05.20) Is Mamba Compatible with Trajectory Optimization in Offline Reinforcement Learning? [Paper](https://arxiv.org/abs/2405.12094)
(Arxiv 24.05.31) Decision Mamba: Reinforcement Learning via Hybrid Selective Sequence Modeling? [Paper](https://arxiv.org/abs/2406.00079)
(Arxiv 24.06.04) EchoMamba4Rec: Harmonizing Bidirectional State Space Models with Spectral Filtering for Advanced Sequential Recommendation [Paper](https://arxiv.org/abs/2406.02638)
(Arxiv 24.06.08) Decision Mamba: A Multi-Grained State Space Model with Self-Evolution Regularization for Offline RL [Paper](https://arxiv.org/abs/2406.05427)
## Diffusion
(Arxiv 24.03.21) ZigMa: Zigzag Mamba Diffusion Model [Paper](https://arxiv.org/abs/2403.13802) [Code](https://github.com/CompVis/zigma) 
\(Arxiv 24.05.05) SMCD: High Realism Motion Style Transfer via Mamba-based Diffusion [Paper](https://arxiv.org/abs/2405.02844)
(Arxiv 24.05.08) VM-DDPM: Vision Mamba Diffusion for Medical Image Synthesis [Paper](https://arxiv.org/abs/2405.05667)
\(Arxiv 24.05.23) DiM: Diffusion Mamba for Efficient High-Resolution Image Synthesis [Paper](https://arxiv.org/abs/2405.14224) [Code](https://github.com/tyshiwo1/DiM-DiffusionMamba/) 
(Arxiv 24.05.24) Scaling Diffusion Mamba with Bidirectional SSMs for Efficient Image and Video Generation [Paper](https://arxiv.org/abs/2405.15881)
(Arxiv 24.05.28) DiG: Scalable and Efficient Diffusion Models with Gated Linear Attention [Paper](https://arxiv.org/abs/2405.18428) [Code](https://github.com/hustvl/DiG) 
(Arxiv 24.06.03) Dimba: Transformer-Mamba Diffusion Models [Paper](https://arxiv.org/abs/2406.01159) [Code](https://github.com/feizc/Dimba) 
(Arxiv 24.06.07) Efficient 3D Shape Generation via Diffusion Mamba with Bidirectional SSMs [Paper](https://arxiv.org/abs/2406.05038) [Code](https://github.com/feizc/Dimba) 
## Embodied AI
(Arxiv 24.06.06) RoboMamba: Multimodal State Space Model for Efficient Robot Reasoning and Manipulation [Paper](https://arxiv.org/abs/2406.04339) [Code](https://github.com/lmzpai/roboMamba) 
## Other Useful Sources
[Mamba_State_Space_Model_Paper_List](https://github.com/Event-AHU/Mamba_State_Space_Model_Paper_List)
[Awesome State-Space Resources for ML](https://github.com/AvivBick/awesome-ssm-ml)
[Awesome-state-space-models](https://github.com/radarFudan/Awesome-state-space-models)
[Video-of-HiPPO](https://slideslive.com/38937809)
[Video-of-Mamba-and-S4-Explained](https://www.youtube.com/watch?v=8Q_tqwpTpVU)
[Mamba-Notes](https://github.com/hkproj/mamba-notes)
[Annotated-Mamba](https://srush.github.io/annotated-mamba/hard.html)
[A Visual Guide to Mamba and State Space Models](https://www.maartengrootendorst.com/blog/mamba/)
## Citation
If you find this repository useful, please consider citing our paper:
```python
@misc{tang2024vmrnn,
title={VMRNN: Integrating Vision Mamba and LSTM for Efficient and Accurate Spatiotemporal Forecasting},
author={Yujin Tang and Peijie Dong and Zhenheng Tang and Xiaowen Chu and Junwei Liang},
year={2024},
eprint={2403.16536},
archivePrefix={arXiv},
primaryClass={cs.CV}
}
```