Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-08T13:40:59.697257Z
Paper Citation Record · LEDGER
As of 8 August 2026, this Paper Citation Record lists 70 of 70 outbound references and 2 inbound Pith citation observations for arXiv:2502.07161.
A citation records a reference. It does not transfer a finding from one paper to another.
Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-08T13:40:59.697257Z
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-05-10T00:09:29.861387Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-10T00:14:46.936853Z
70 of 70 outbound references displayed
External citation measurements
No source-named external measurement is stored.
Observation cefe63ef-ecd6-4495-a063-88fd25eaa985 · outbound
A Survey on Mamba Architecture for Vision Applications What Makes Convolutional Models Great on Long Sequence Modeling?
Reference 1
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Observation 946b2f0e-dbd5-4ace-8480-4479084deecf · outbound
A Survey on Mamba Architecture for Vision Applications Time-aware large kernel convolutions,
Reference 2
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Observation 9aa4553e-9c9b-4844-9f33-e0c09463311c · outbound
A Survey on Mamba Architecture for Vision Applications Depth-wise convolutions in vision transformers for efficient training on small datasets,
Reference 3
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Observation 93632301-974e-4a00-8c12-b935852a7420 · outbound
A Survey on Mamba Architecture for Vision Applications Attention is all you need,
Reference 4
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Observation a8cfab20-75bd-4410-9d36-bf70a350d342 · outbound
A Survey on Mamba Architecture for Vision Applications An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale
Reference 5
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Observation 0aeee6dc-2f9c-4baf-9e66-8639063747db · outbound
A Survey on Mamba Architecture for Vision Applications Predicting therapeutic response to hypoglossal nerve stimulation using deep learning,
Reference 6
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Observation dc57be17-aa17-400e-ac97-75378015f307 · outbound
A Survey on Mamba Architecture for Vision Applications Aphid cluster recognition and detection in the wild using deep learning models,
Reference 7
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Observation 78c84e5c-baa4-48fa-9fdb-f5daddf8194d · outbound
A Survey on Mamba Architecture for Vision Applications A new dataset and comparative study for aphid cluster detection and segmentation in sorghum fields,
Reference 8
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Observation be81930b-5d87-47e4-96f6-f21c0be41304 · outbound
A Survey on Mamba Architecture for Vision Applications Edge-aware multi-task network for integrating quantification segmentation and uncertainty prediction of liver tumor on multi-modality non-contrast mri,
Reference 9
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Observation b298cb7a-af43-4d37-b9a1-9bb63d597aee · outbound
A Survey on Mamba Architecture for Vision Applications Deep residual learning for image recognition,
Reference 10
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Observation a14e83cd-fe0e-49e7-b33e-ea10188ca7fc · outbound
A Survey on Mamba Architecture for Vision Applications Is space-time attention all you need for video understanding?
Reference 11
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Observation ddb7fb22-0ed0-4074-bd5d-6897ab9498cb · outbound
A Survey on Mamba Architecture for Vision Applications Generating Long Sequences with Sparse Transformers
Reference 12
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Observation effa2afa-7e40-4027-ac66-3d2b4231d98b · outbound
A Survey on Mamba Architecture for Vision Applications Xcit: Cross- covariance image transformers,
Reference 13
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Observation 2b424ceb-5029-4eb2-9119-b51543955b54 · outbound
A Survey on Mamba Architecture for Vision Applications Mamba: Linear-Time Sequence Modeling with Selective State Spaces
Reference 14
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Observation 79fa4be1-de52-46e9-ba8f-2b9654e433a6 · outbound
A Survey on Mamba Architecture for Vision Applications Vision Mamba: Efficient Visual Representation Learning with Bidirectional State Space Model
Reference 15
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Observation 790f8a8a-894f-4dc3-a087-65cadd65e5b0 · outbound
A Survey on Mamba Architecture for Vision Applications Videomamba: State space model for efficient video understanding,
Reference 16
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Observation 28839067-d9f1-4609-8c4f-c7f713aa9cb3 · outbound
A Survey on Mamba Architecture for Vision Applications A Survey of Mamba
Reference 17
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Observation 84847436-d64a-4607-be1f-9182ccbe17d0 · outbound
A Survey on Mamba Architecture for Vision Applications Mamba-360: Survey of State Space Models as Transformer Alternative for Long Sequence Modelling: Methods, Applications, and Challenges
Reference 18
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Observation eb8b7b09-1e22-4e4d-a9a4-04db05f7b940 · outbound
A Survey on Mamba Architecture for Vision Applications MedMamba: Vision Mamba for Medical Image Classification
Reference 19
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Observation ef036012-28e5-472a-99a7-02689247054b · outbound
A Survey on Mamba Architecture for Vision Applications A comprehensive survey of mamba architectures for medical image analysis: Classification, segmentation, restoration and beyond,
Reference 20
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Observation dd98d46c-61c6-4ba6-82ba-c6b1683e7117 · outbound
A Survey on Mamba Architecture for Vision Applications Visual Mamba: A Survey and New Outlooks
Reference 21
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Observation 209bdb1a-5b3b-4531-b31e-9ced1b8ffc40 · outbound
A Survey on Mamba Architecture for Vision Applications A survey on visual mamba,
Reference 22
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Observation ca2b8b02-d2b3-4aaf-9a01-bc324c755d88 · outbound
A Survey on Mamba Architecture for Vision Applications Comparison between first-order hold with zero-order hold in discretization of input-delay nonlinear systems,
Reference 23
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Observation 4178db16-4df7-48bd-bd70-7499ba93dcfa · outbound
A Survey on Mamba Architecture for Vision Applications VMamba: Visual State Space Model
Reference 24
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Observation 71d6637c-3fbe-48c3-903f-27798fb6665f · outbound
A Survey on Mamba Architecture for Vision Applications Mamba-R: Vision Mamba ALSO Needs Registers
Reference 25
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Observation 575f7fcb-4d09-475b-bf49-3b94dd235682 · outbound
A Survey on Mamba Architecture for Vision Applications VSSD: Vision Mamba with Non-Causal State Space Duality
Reference 26
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Observation 2e9b1379-f5ff-477a-bfad-fc34f214b0fc · outbound
A Survey on Mamba Architecture for Vision Applications LocalMamba: Visual State Space Model with Windowed Selective Scan
Reference 27
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Observation bb0b2c40-ee28-4d2a-be3b-30faf05b9f70 · outbound
A Survey on Mamba Architecture for Vision Applications Mamba2d: A natively multi-dimensional state-space model for vision tasks,
Reference 28
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Observation 2ba82ae4-3dde-4f04-80c6-c3ae013c5d22 · outbound
A Survey on Mamba Architecture for Vision Applications EfficientViM: Efficient Vision Mamba with Hidden State Mixer based State Space Duality
Reference 29
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Observation 52e3f2ff-15d6-47ed-a90d-4a5e1fa59d20 · outbound
A Survey on Mamba Architecture for Vision Applications Transformers are SSMs: Generalized Models and Efficient Algorithms Through Structured State Space Duality
Reference 30
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Observation 971af3c4-120e-49d2-bcac-589d806e7f38 · outbound
A Survey on Mamba Architecture for Vision Applications Vivit: A video vision transformer,
Reference 31
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Observation 94e6b906-42fc-491c-937f-b05e4922fbe3 · outbound
A Survey on Mamba Architecture for Vision Applications Snakes and Ladders: Two Steps Up for VideoMamba
Reference 32
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Observation d0446e20-d227-437c-8b4e-437b6bc0d3e1 · outbound
A Survey on Mamba Architecture for Vision Applications Video Mamba Suite: State Space Model as a Versatile Alternative for Video Understanding
Reference 33
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Observation 47fba5fc-418b-4aa9-ad4e-4b70fa6bacaf · outbound
A Survey on Mamba Architecture for Vision Applications Vivim: a Video Vision Mamba for Medical Video Segmentation
Reference 34
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Observation 0b6d21ac-d807-4230-8ab2-42e52d94e3b5 · outbound
A Survey on Mamba Architecture for Vision Applications Imagenet classification with deep convolutional neural networks,
Reference 35
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Observation b7938c73-9912-4c92-bcfc-5042630e53e6 · outbound
A Survey on Mamba Architecture for Vision Applications Object detection with deep learning: A review,
Reference 36
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Observation 5854be4b-aa08-4cf7-846a-5f0baa6b7272 · outbound
A Survey on Mamba Architecture for Vision Applications Unified perceptual parsing for scene understanding,
Reference 37
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Observation 9fc27851-cfc1-456d-af44-1a5e01e85e99 · outbound
A Survey on Mamba Architecture for Vision Applications Meth- ods and datasets on semantic segmentation: A review,
Reference 38
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Observation 2709c6f9-7e44-42e3-9b95-3439d6531afa · outbound
A Survey on Mamba Architecture for Vision Applications A brief survey on semantic segmentation with deep learning,
Reference 39
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Observation ad883d6d-6d29-4db0-a921-0bba7ab9c90b · outbound
A Survey on Mamba Architecture for Vision Applications Neural Architecture Search based Global-local Vision Mamba for Palm-Vein Recognition
Reference 40
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Observation 4754307d-0ad8-4e5f-947a-81b62369a1ea · outbound
A Survey on Mamba Architecture for Vision Applications Venturing into Uncharted Waters: The Navigation Compass from Transformer to Mamba
Reference 41
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Observation 26a8c319-3df8-4730-864f-38db2a855715 · outbound
A Survey on Mamba Architecture for Vision Applications MambaBEV: An EV-based 3D detection model with Mamba2
Reference 42
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Observation 3cd8286c-9eff-4435-a197-d8b359240a3c · outbound
A Survey on Mamba Architecture for Vision Applications PlainMamba: Improving Non-Hierarchical Mamba in Visual Recognition
Reference 43
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Observation 288e5ca1-92af-4478-9942-a9a8e1dc6137 · outbound
A Survey on Mamba Architecture for Vision Applications Spatial-Mamba: Effective Visual State Space Models via Structure-aware State Fusion
Reference 44
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Observation a2cdb792-40f2-4704-bd79-15df2e205a70 · outbound
A Survey on Mamba Architecture for Vision Applications Famba-V: Fast Vision Mamba with Cross-Layer Token Fusion
Reference 45
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Observation e348e3e8-bf82-49c4-8df9-a58e5327f133 · outbound
A Survey on Mamba Architecture for Vision Applications Towards accurate post-training quantization for vision transformer,
Reference 46
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Observation 3dd8351c-d96c-4f16-8722-4438b50dd360 · outbound
A Survey on Mamba Architecture for Vision Applications Token Merging: Your ViT But Faster
Reference 47
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Observation c2cc6f93-3ff4-4c25-a630-e9e490d7563b · outbound
A Survey on Mamba Architecture for Vision Applications PuMer: Pruning and Merging Tokens for Efficient Vision Language Models
Reference 48
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Observation c526bfd0-aa12-4f97-8638-f3d729e9a41d · outbound
A Survey on Mamba Architecture for Vision Applications Hi-Mamba: Hierarchical Mamba for Efficient Image Super-Resolution
Reference 49
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Observation d33a8e67-4932-4eb1-a354-e2994e19ab3a · outbound
A Survey on Mamba Architecture for Vision Applications Efficiently Modeling Long Sequences with Structured State Spaces
Reference 50
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Observation ef1cd1dd-f80a-4607-b975-bdf65f8667e4 · outbound
A Survey on Mamba Architecture for Vision Applications Mask r-cnn,
Reference 51
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Observation 07bb3982-387a-4388-b724-9f9c0b173966 · outbound
A Survey on Mamba Architecture for Vision Applications Imagenet: A large-scale hierarchical image database,
Reference 52
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Observation aa0e6627-1a06-4706-97a2-d376a09ae8e6 · outbound
A Survey on Mamba Architecture for Vision Applications Semantic understanding of scenes through the ade20k dataset,
Reference 53
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Observation 45e729d5-c3b4-4c09-99ac-bd511b3632e1 · outbound
A Survey on Mamba Architecture for Vision Applications Microsoft coco: Common objects in context,
Reference 54
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Observation aa0d2196-c9df-48fe-8bb3-a07933ead893 · outbound
A Survey on Mamba Architecture for Vision Applications The Kinetics Human Action Video Dataset
Reference 55
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Observation bdeab26d-9ee4-4718-88d6-ae526c667bb2 · outbound
A Survey on Mamba Architecture for Vision Applications Quo vadis, action recognition? a new model and the kinetics dataset,
Reference 56
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Observation 579b4497-7fdd-4bcb-8b86-c4c1e5b0cb38 · outbound
A Survey on Mamba Architecture for Vision Applications The” something something
Reference 57
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Observation cebced32-002d-4a55-891c-36a33637cca8 · outbound
A Survey on Mamba Architecture for Vision Applications Masked-attention mask transformer for universal image segmentation,
Reference 58
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Observation 41ec4869-cbb5-4a6e-a287-54e6f475e483 · outbound
A Survey on Mamba Architecture for Vision Applications FlowMamba: Learning Point Cloud Scene Flow with Global Motion Propagation
Reference 59
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Observation d35c39d5-109c-4a77-b87f-628952b870c5 · outbound
A Survey on Mamba Architecture for Vision Applications Pv-ssm: Exploring pure visual state space model for high-dimensional medical data analysis,
Reference 60
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Observation 4a12e345-f469-4ac2-839f-8cfb3582ea43 · outbound
A Survey on Mamba Architecture for Vision Applications MambaU-Lite: A Lightweight Model based on Mamba and Integrated Channel-Spatial Attention for Skin Lesion Segmentation
Reference 61
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Observation 521a8c6a-ac4e-48a3-a2f2-faaade30ec32 · outbound
A Survey on Mamba Architecture for Vision Applications Shuffle mamba: State space models with random shuffle for multi-modal image fusion,
Reference 62
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Observation 47bc694a-3889-4e68-bca2-6584b7fd8294 · outbound
A Survey on Mamba Architecture for Vision Applications MambaSOD: Dual Mamba-Driven Cross-Modal Fusion Network for RGB-D Salient Object Detection
Reference 63
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Observation 61474d01-7a16-4996-9b52-af9784f6ee83 · outbound
A Survey on Mamba Architecture for Vision Applications NIMBA: Towards Robust and Principled Processing of Point Clouds With SSMs
Reference 64
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Observation e9a7d187-c4ef-4ffd-8134-5ccaa0547388 · outbound
A Survey on Mamba Architecture for Vision Applications Serialized Point Mamba: A Serialized Point Cloud Mamba Segmentation Model
Reference 65
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Observation a3fd4c72-53c0-45d0-aa1d-0414c9a00486 · outbound
A Survey on Mamba Architecture for Vision Applications Mamba YOLO: A Simple Baseline for Object Detection with State Space Model
Reference 66
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Observation 88371fa8-2444-4bb9-abf7-d92e7dc96143 · outbound
A Survey on Mamba Architecture for Vision Applications Pillarmamba: A lightweight mamba-based model for 3d object detection,
Reference 67
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Observation e5a74ee5-a612-4744-ac26-c9103f4cc6ab · outbound
A Survey on Mamba Architecture for Vision Applications MambaDETR: Query-based Temporal Modeling using State Space Model for Multi-View 3D Object Detection
Reference 68
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Observation fad22f8c-1f0f-407d-a562-b8863431b45a · outbound
A Survey on Mamba Architecture for Vision Applications MambaTron: Efficient Cross-Modal Point Cloud Enhancement using Aggregate Selective State Space Modeling
Reference 69
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Observation 27d0e446-e4db-45be-a137-e12ba369ea14 · outbound
A Survey on Mamba Architecture for Vision Applications Ms-temba: Multi- scale temporal mamba for efficient temporal action detection,
Reference 70
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Observation e85c4644-c370-440e-9e89-e0515dcc2b74 · inbound
Beyond ZOH: Advanced Discretization Strategies for Vision Mamba A Survey on Mamba Architecture for Vision Applications
Reference 14
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Observation 5179b57a-776a-44ce-8f68-d0ef73bf5b05 · inbound
ViM-Q: Scalable Algorithm-Hardware Co-Design for Vision Mamba Model Inference on FPGA A Survey on Mamba Architecture for Vision Applications
Reference 21
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