A2Mamba: Attention-augmented State Space Models for Visual Recognition | Paper Citation Record

Observation ba1fdd7c-b8ef-4ae5-b875-624c69aac48e · outbound

This paper cites An image is worth 16x16 words: Transformers for image recognition at scale,.

A2Mamba: Attention-augmented State Space Models for Visual Recognition An image is worth 16x16 words: Transformers for image recognition at scale,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:09:52.587508Z

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Observation 9fd7222a-87d3-49fc-ae91-5ee4fd5d73b3 · outbound

This paper cites Attention is all you need,.

A2Mamba: Attention-augmented State Space Models for Visual Recognition Attention is all you need,

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-06T15:09:50.764415Z

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Observation 5a0c9534-c898-4c96-ae12-cde4dc06bb54 · outbound

This paper cites Swin transformer: Hierarchical vision transformer using shifted windows,.

A2Mamba: Attention-augmented State Space Models for Visual Recognition Swin transformer: Hierarchical vision transformer using shifted windows,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:09:52.553586Z

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Observation 91e928d6-afbe-4b30-bf04-4f5c6f7c0741 · outbound

This paper cites Cswin transformer: A general vision transformer back- bone with cross-shaped windows,.

A2Mamba: Attention-augmented State Space Models for Visual Recognition Cswin transformer: A general vision transformer back- bone with cross-shaped windows,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:09:52.530805Z

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Observation 90bb7a0d-0293-48c4-a2cf-ad55cc744dcd · outbound

This paper cites Neighborhood attention transformer,.

A2Mamba: Attention-augmented State Space Models for Visual Recognition Neighborhood attention transformer,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:09:52.511526Z

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Observation e194ed73-7e65-44b9-aa32-fb0e5c0e8b24 · outbound

This paper cites Biformer: Vi- sion transformer with bi-level routing attention,.

A2Mamba: Attention-augmented State Space Models for Visual Recognition Biformer: Vi- sion transformer with bi-level routing attention,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:09:52.490935Z

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Observation 69600ac6-8669-4edd-89a7-9e1767173642 · outbound

This paper cites Pyramid vision transformer: A versatile backbone for dense prediction without convolutions,.

A2Mamba: Attention-augmented State Space Models for Visual Recognition Pyramid vision transformer: A versatile backbone for dense prediction without convolutions,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:09:52.472142Z

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Observation 48ea8bfe-c03a-46a9-b463-4c3e6dc5c8fc · outbound

This paper cites Pvt v2: Improved baselines with pyramid vision transformer,.

A2Mamba: Attention-augmented State Space Models for Visual Recognition Pvt v2: Improved baselines with pyramid vision transformer,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:09:52.456654Z

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Observation 42af6379-759d-4df4-a9ba-3f52adeea1f4 · outbound

This paper cites P2t: Pyramid pool- ing transformer for scene understanding,.

A2Mamba: Attention-augmented State Space Models for Visual Recognition P2t: Pyramid pool- ing transformer for scene understanding,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:09:52.438189Z

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Observation e2a9d607-f532-44de-be37-c92db3b21012 · outbound

This paper cites Maxvit: Multi-axis vision transformer,.

A2Mamba: Attention-augmented State Space Models for Visual Recognition Maxvit: Multi-axis vision transformer,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:09:52.416711Z

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Observation 425f7171-96a9-4ff0-bf45-25fcb391a43f · outbound

This paper cites Dilated Neighborhood Attention Transformer.

A2Mamba: Attention-augmented State Space Models for Visual Recognition Dilated Neighborhood Attention Transformer

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-06T15:09:50.841599Z

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Observation eb1f1f34-e488-40a4-a43d-61924b7f96db · outbound

This paper cites Crossformer++: A versatile vision transformer hinging on cross-scale attention,.

A2Mamba: Attention-augmented State Space Models for Visual Recognition Crossformer++: A versatile vision transformer hinging on cross-scale attention,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:09:52.397720Z

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Observation 972e4b1f-57f5-4cff-a704-5540e80333e5 · outbound

This paper cites Mamba: Linear-time sequence modeling with selective state spaces,.

A2Mamba: Attention-augmented State Space Models for Visual Recognition Mamba: Linear-time sequence modeling with selective state spaces,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:09:52.378973Z

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Observation fda5f9af-b025-4671-8c11-1e061f9781c6 · outbound

This paper cites Vision mamba: Efficient visual representation learning with bidirectional state space model,.

A2Mamba: Attention-augmented State Space Models for Visual Recognition Vision mamba: Efficient visual representation learning with bidirectional state space model,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:09:52.362085Z

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Observation f7038946-8832-44ce-a7f3-0e16ff3b39b0 · outbound

This paper cites Vmamba: Visual state space model,.

A2Mamba: Attention-augmented State Space Models for Visual Recognition Vmamba: Visual state space model,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:09:52.343974Z

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Observation ef7d6c22-1b9c-4e94-b8d7-c9937863cd15 · outbound

This paper cites Local- mamba: Visual state space model with windowed selective scan,.

A2Mamba: Attention-augmented State Space Models for Visual Recognition Local- mamba: Visual state space model with windowed selective scan,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:09:52.326198Z

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Observation 23405231-0106-4be3-aa04-624a87bafbdb · outbound

This paper cites Plainmamba: Improving non-hierarchical mamba in visual recognition,.

A2Mamba: Attention-augmented State Space Models for Visual Recognition Plainmamba: Improving non-hierarchical mamba in visual recognition,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:09:52.302606Z

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Observation d6351ae5-d90f-4a5a-ba72-e57c5cba56d4 · outbound

This paper cites Efficientvmamba: Atrous selective scan for light weight visual mamba,.

A2Mamba: Attention-augmented State Space Models for Visual Recognition Efficientvmamba: Atrous selective scan for light weight visual mamba,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:09:52.285332Z

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Observation 5d5a3d7c-0e70-4714-bcc4-b83f500f290f · outbound

This paper cites Spatial- mamba: Effective visual state space models via structure-aware state fusion,.

A2Mamba: Attention-augmented State Space Models for Visual Recognition Spatial- mamba: Effective visual state space models via structure-aware state fusion,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:09:52.268053Z

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Observation ca6aa5af-2f29-47b1-a327-38d439e0e016 · outbound

This paper cites Sparx: A sparse cross-layer connec- tion mechanism for hierarchical vision mamba and transformer networks,.

A2Mamba: Attention-augmented State Space Models for Visual Recognition Sparx: A sparse cross-layer connec- tion mechanism for hierarchical vision mamba and transformer networks,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:09:52.250146Z

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Observation f8bdf14b-006b-4c1d-9e15-d4a510ae5670 · outbound

This paper cites Mambaout: Do we really need mamba for vision?,.

A2Mamba: Attention-augmented State Space Models for Visual Recognition Mambaout: Do we really need mamba for vision?,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:09:52.234059Z

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Observation 6368990a-c1ab-47c8-b502-0282822c9fcf · outbound

This paper cites Mambavision: A hybrid mamba- transformer vision backbone,.

A2Mamba: Attention-augmented State Space Models for Visual Recognition Mambavision: A hybrid mamba- transformer vision backbone,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:09:52.216562Z

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Observation 6a5ba455-6841-4422-a19f-c1a49a949798 · outbound

This paper cites Demystify mamba in vision: A linear attention perspective,.

A2Mamba: Attention-augmented State Space Models for Visual Recognition Demystify mamba in vision: A linear attention perspective,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:09:52.197316Z

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Observation b55cebee-0fea-45c4-9841-54e174216143 · outbound

This paper cites Metaformer baselines for vision,.

A2Mamba: Attention-augmented State Space Models for Visual Recognition Metaformer baselines for vision,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:09:52.179234Z

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Observation c1f11d95-901e-4b9e-a2cb-7e116bb1f065 · outbound

This paper cites Rmt: Retentive networks meet vision transformers,.

A2Mamba: Attention-augmented State Space Models for Visual Recognition Rmt: Retentive networks meet vision transformers,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:09:52.161542Z

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Observation 7a1b6fdc-d592-462e-b1e5-baeb59967042 · outbound

This paper cites Transnext: Robust foveal visual perception for vision transformers,.

A2Mamba: Attention-augmented State Space Models for Visual Recognition Transnext: Robust foveal visual perception for vision transformers,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:09:52.144547Z

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Observation c283b729-c639-4132-b377-402c337976f7 · outbound

This paper cites Segman: Omni-scale context modeling with state space models and local attention for semantic segmen- tation,.

A2Mamba: Attention-augmented State Space Models for Visual Recognition Segman: Omni-scale context modeling with state space models and local attention for semantic segmen- tation,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:09:52.127454Z

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Observation 6e1883ae-0c0d-4f15-bd0b-554fe884baa4 · outbound

This paper cites Unified perceptual parsing for scene understanding,.

A2Mamba: Attention-augmented State Space Models for Visual Recognition Unified perceptual parsing for scene understanding,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:09:52.110031Z

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Observation dd1761c8-0f0a-4f4c-b510-08999a30cd0f · outbound

This paper cites Cascade r-cnn: High quality object detection and instance segmentation,.

A2Mamba: Attention-augmented State Space Models for Visual Recognition Cascade r-cnn: High quality object detection and instance segmentation,

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:09:52.093189Z

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Observation 00b3a207-6d1d-4489-ba75-28ba9edb9213 · outbound

This paper cites Moganet: Multi-order gated aggregation network,.

A2Mamba: Attention-augmented State Space Models for Visual Recognition Moganet: Multi-order gated aggregation network,

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:09:52.075347Z

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Observation 7dbe8029-f3a1-47f1-9d31-cf2c491db886 · outbound

This paper cites Imagenet classifica- tion with deep convolutional neural networks,.

A2Mamba: Attention-augmented State Space Models for Visual Recognition Imagenet classifica- tion with deep convolutional neural networks,

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:09:52.055737Z

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Observation 28ac3b53-c809-4ce7-98dc-a24988dd79de · outbound

This paper cites Very deep convolutional net- works for large-scale image recognition,.

A2Mamba: Attention-augmented State Space Models for Visual Recognition Very deep convolutional net- works for large-scale image recognition,

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:09:52.037721Z

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Observation 5d393ba6-29d0-4826-a9ee-cad7b07bbddd · outbound

This paper cites Deep residual learning for image recognition,.

A2Mamba: Attention-augmented State Space Models for Visual Recognition Deep residual learning for image recognition,

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:09:52.019935Z

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Observation 7f605f21-1755-4124-ba03-41a201580d8f · outbound

This paper cites Densely connected convolutional networks,.

A2Mamba: Attention-augmented State Space Models for Visual Recognition Densely connected convolutional networks,

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:09:52.001879Z

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Observation cb93ccad-6b2f-4b64-8608-7220e8cd1d3a · outbound

This paper cites Convnext v2: Co-designing and scaling convnets with masked autoencoders,.

A2Mamba: Attention-augmented State Space Models for Visual Recognition Convnext v2: Co-designing and scaling convnets with masked autoencoders,

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:09:51.981255Z

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Observation 643adcb0-7999-4429-8c78-13328e67386c · outbound

This paper cites More convnets in the 2020s: Scaling up kernels beyond 51x51 using sparsity,.

A2Mamba: Attention-augmented State Space Models for Visual Recognition More convnets in the 2020s: Scaling up kernels beyond 51x51 using sparsity,

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:09:51.964054Z

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Observation 12aa3452-af55-4f98-bf1e-a7190b28c1f8 · outbound

This paper cites Unireplknet: A universal perception large-kernel convnet for audio, video, point cloud, time-series and image recognition,.

A2Mamba: Attention-augmented State Space Models for Visual Recognition Unireplknet: A universal perception large-kernel convnet for audio, video, point cloud, time-series and image recognition,

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:09:51.946801Z

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Observation 16d376bf-0f05-45a5-94f3-2c84c3228c15 · outbound

This paper cites Pelk: Parameter- efficient large kernel convnets with peripheral convolution,.

A2Mamba: Attention-augmented State Space Models for Visual Recognition Pelk: Parameter- efficient large kernel convnets with peripheral convolution,

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:09:51.931226Z

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Observation a1529784-b230-4f1e-aebe-9ac2981dff83 · outbound

This paper cites Hor- net: Efficient high-order spatial interactions with recursive gated convolutions,.

A2Mamba: Attention-augmented State Space Models for Visual Recognition Hor- net: Efficient high-order spatial interactions with recursive gated convolutions,

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:09:51.914539Z

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Observation ec5c3836-9a92-4a90-84b5-99cad8f21673 · outbound

This paper cites Focal modulation networks,.

A2Mamba: Attention-augmented State Space Models for Visual Recognition Focal modulation networks,

Reference 40

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Observation b19a8034-6077-43f6-b0b2-e0034dd3e4d5 · outbound

This paper cites Overlock: An overview-first-look-closely-next convnet with context-mixing dynamic kernels,.

A2Mamba: Attention-augmented State Space Models for Visual Recognition Overlock: An overview-first-look-closely-next convnet with context-mixing dynamic kernels,

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:09:51.884669Z

Source-reported events for the cited work

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Observation a9ec3333-e050-4969-9012-0a98f571db77 · outbound

This paper cites Neural mech- anisms of visual attention: how top-down feedback highlights relevant locations,.

A2Mamba: Attention-augmented State Space Models for Visual Recognition Neural mech- anisms of visual attention: how top-down feedback highlights relevant locations,

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:09:51.865847Z

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Observation 5128317b-447b-44c9-9275-87a9cb64838a · outbound

This paper cites Cmt: Convolutional neural networks meet vision transformers,.

A2Mamba: Attention-augmented State Space Models for Visual Recognition Cmt: Convolutional neural networks meet vision transformers,

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:09:51.846467Z

Source-reported events for the cited work

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Observation 0880391d-1485-4ac4-a046-533ffcf4671f · outbound

This paper cites On the integration of self-attention and convolution,.

A2Mamba: Attention-augmented State Space Models for Visual Recognition On the integration of self-attention and convolution,

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:09:51.827723Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 91fcc3f0-373d-48e3-a882-8720fe7ce769 · outbound

This paper cites Mixformer: Mixing features across windows and dimensions,.

A2Mamba: Attention-augmented State Space Models for Visual Recognition Mixformer: Mixing features across windows and dimensions,

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:09:51.810651Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 03545270-c0f6-455b-8846-c95e9f04cca2 · outbound

This paper cites Transxnet: Learning both global and local dynamics with a dual dynamic token mixer for visual recognition,.

A2Mamba: Attention-augmented State Space Models for Visual Recognition Transxnet: Learning both global and local dynamics with a dual dynamic token mixer for visual recognition,

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:09:51.792466Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 22569066-d2e4-4aba-8a01-8d3646242ba6 · outbound

This paper cites Uniformer: Unifying convolution and self-attention for visual recognition,.

A2Mamba: Attention-augmented State Space Models for Visual Recognition Uniformer: Unifying convolution and self-attention for visual recognition,

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:09:51.775741Z

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Observation 6f8883ff-dde9-4f66-a727-bb50269aacca · outbound

This paper cites Scene parsing through ade20k dataset,.

A2Mamba: Attention-augmented State Space Models for Visual Recognition Scene parsing through ade20k dataset,

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:09:51.759881Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation f86d9b79-7c75-4220-8ecb-4bec17e5f0e2 · outbound

This paper cites The cityscapes dataset for semantic urban scene understanding,.

A2Mamba: Attention-augmented State Space Models for Visual Recognition The cityscapes dataset for semantic urban scene understanding,

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:09:51.742741Z

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Observation 8c82a540-b78c-4408-81cb-d6867040d5cb · outbound

This paper cites Microsoft coco: Common objects in context,.

A2Mamba: Attention-augmented State Space Models for Visual Recognition Microsoft coco: Common objects in context,

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:09:51.726710Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 77bbea64-1a7a-4227-b7fc-50e7b8144e1d · outbound

This paper cites Segnext: Rethinking convolutional attention design for semantic segmentation,.

A2Mamba: Attention-augmented State Space Models for Visual Recognition Segnext: Rethinking convolutional attention design for semantic segmentation,

Reference 51

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Source-reported events for the cited work

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Observation d9196c39-f9e7-4554-88cf-07431370702b · outbound

This paper cites Multi-scale representations by varying window attention for semantic segmentation,.

A2Mamba: Attention-augmented State Space Models for Visual Recognition Multi-scale representations by varying window attention for semantic segmentation,

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:09:51.699539Z

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Observation 15439f9d-68ef-4eae-94d9-f8291e155b51 · outbound

This paper cites A convnet for the 2020s,.

A2Mamba: Attention-augmented State Space Models for Visual Recognition A convnet for the 2020s,

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:09:51.684223Z

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Observation f0e22b52-5ef7-4558-a626-20735c413c99 · outbound

This paper cites Deeplab: Semantic image segmentation with deep convo- lutional nets, atrous convolution, and fully connected crfs,.

A2Mamba: Attention-augmented State Space Models for Visual Recognition Deeplab: Semantic image segmentation with deep convo- lutional nets, atrous convolution, and fully connected crfs,

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:09:51.668970Z

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Observation b4c18396-b865-458c-957e-6f0116169af8 · outbound

This paper cites Segformer: Simple and efficient design for semantic segmenta- tion with transformers,.

A2Mamba: Attention-augmented State Space Models for Visual Recognition Segformer: Simple and efficient design for semantic segmenta- tion with transformers,

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:09:51.651635Z

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Observation 8ede2beb-da45-4abe-9517-98d23d432cee · outbound

This paper cites Encoder-decoder with atrous separable convolution for semantic image segmentation,.

A2Mamba: Attention-augmented State Space Models for Visual Recognition Encoder-decoder with atrous separable convolution for semantic image segmentation,

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:09:51.635160Z

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Observation fd6975bf-1120-470f-b34b-2751e263d2e5 · outbound

This paper cites Quadmamba: Learning quadtree-based selective scan for visual state space model,.

A2Mamba: Attention-augmented State Space Models for Visual Recognition Quadmamba: Learning quadtree-based selective scan for visual state space model,

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:09:51.618075Z

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Observation df65a1c4-3f36-40a0-a9d9-0d426726c940 · outbound

This paper cites Inceptionnext: When incep- tion meets convnext,.

A2Mamba: Attention-augmented State Space Models for Visual Recognition Inceptionnext: When incep- tion meets convnext,

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:09:51.600605Z

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Observation 91ffedd3-ea61-412c-a24e-b180ae6ba3d7 · outbound

This paper cites Multi-scale vmamba: Hierarchy in hierarchy visual state space model,.

A2Mamba: Attention-augmented State Space Models for Visual Recognition Multi-scale vmamba: Hierarchy in hierarchy visual state space model,

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:09:51.584071Z

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Observation 1a444a73-e66f-4558-9edc-9db3477f0f6c · outbound

This paper cites Densenets reloaded: Paradigm shift beyond resnets and vits,.

A2Mamba: Attention-augmented State Space Models for Visual Recognition Densenets reloaded: Paradigm shift beyond resnets and vits,

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:09:51.568557Z

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Observation cff5d136-c713-420b-acfd-8457efa018e9 · outbound

This paper cites Regionvit: Regional-to-local attention for vision transformers,.

A2Mamba: Attention-augmented State Space Models for Visual Recognition Regionvit: Regional-to-local attention for vision transformers,

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:09:51.550163Z

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Observation 2f4e69f1-b3ae-406d-97c4-aefc8daa60ec · outbound

This paper cites Mpvit: Multi-path vision transformer for dense prediction,.

A2Mamba: Attention-augmented State Space Models for Visual Recognition Mpvit: Multi-path vision transformer for dense prediction,

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:09:51.533753Z

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Observation a87df564-05ff-4907-9655-48194ac3c1dc · outbound

This paper cites Conv2former: A simple transformer-style convnet for visual recognition,.

A2Mamba: Attention-augmented State Space Models for Visual Recognition Conv2former: A simple transformer-style convnet for visual recognition,

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:09:51.517351Z

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Observation ee731c59-0194-4631-9c26-0dc15ff27d6c · outbound

This paper cites Scale-aware modula- tion meet transformer,.

A2Mamba: Attention-augmented State Space Models for Visual Recognition Scale-aware modula- tion meet transformer,

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:09:51.501947Z

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Observation df2dcf6a-2ae8-4a98-ada7-cad407c44a59 · outbound

This paper cites Internimage: Exploring large-scale vision foun- dation models with deformable convolutions,.

A2Mamba: Attention-augmented State Space Models for Visual Recognition Internimage: Exploring large-scale vision foun- dation models with deformable convolutions,

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:09:51.486061Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 01cdc303-15fb-46fd-8bcd-fa1ffa637835 · outbound

This paper cites Imagenet: A large-scale hierarchical image database,.

A2Mamba: Attention-augmented State Space Models for Visual Recognition Imagenet: A large-scale hierarchical image database,

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:09:51.469534Z

Source-reported events for the cited work

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Observation 46f210e5-d794-453a-8ebe-babcbc98809e · outbound

This paper cites Decoupled Weight Decay Regularization.

A2Mamba: Attention-augmented State Space Models for Visual Recognition Decoupled Weight Decay Regularization

Reference 67

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Observation b7ff434e-4060-49aa-b7ad-82623b732131 · outbound

This paper cites Deep networks with stochastic depth,.

A2Mamba: Attention-augmented State Space Models for Visual Recognition Deep networks with stochastic depth,

Reference 68

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:09:51.453571Z

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Observation b5860b4b-f80e-4c06-937c-fcdf935e81c4 · outbound

This paper cites Mask r-cnn,.

A2Mamba: Attention-augmented State Space Models for Visual Recognition Mask r-cnn,

Reference 69

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:09:51.437919Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation c2f1edf9-e4f1-44d5-97c8-2e0eebb8890a · outbound

This paper cites Embedding-free transformer with inference spatial reduction for efficient semantic segmentation,.

A2Mamba: Attention-augmented State Space Models for Visual Recognition Embedding-free transformer with inference spatial reduction for efficient semantic segmentation,

Reference 70

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:09:51.423000Z

Source-reported events for the cited work

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Observation a773eba3-3765-45f9-9fb1-3918a217b3dc · outbound

This paper cites Context-guided spatial feature reconstruction for efficient semantic segmentation,.

A2Mamba: Attention-augmented State Space Models for Visual Recognition Context-guided spatial feature reconstruction for efficient semantic segmentation,

Reference 71

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:09:51.408059Z

Source-reported events for the cited work

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Observation f50bed9d-a8f6-48ac-aa4d-03d8ff13f6bb · outbound

This paper cites Vit-comer: Vision transformer with convolutional multi-scale feature interaction for dense predictions,.

A2Mamba: Attention-augmented State Space Models for Visual Recognition Vit-comer: Vision transformer with convolutional multi-scale feature interaction for dense predictions,

Reference 72

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:09:51.391151Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation f2f1046e-3227-4edd-971d-a508d6c615a4 · outbound

This paper cites Object-contextual representations for semantic segmentation,.

A2Mamba: Attention-augmented State Space Models for Visual Recognition Object-contextual representations for semantic segmentation,

Reference 73

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:09:51.374085Z

Source-reported events for the cited work

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Observation a9f4f958-a50d-4d1d-8478-724084523eb3 · outbound

This paper cites Per-pixel classification is not all you need for semantic segmentation,.

A2Mamba: Attention-augmented State Space Models for Visual Recognition Per-pixel classification is not all you need for semantic segmentation,

Reference 74

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:09:51.354809Z

Source-reported events for the cited work

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Observation b7fce7ff-c498-4fad-8179-26fae062073f · outbound

This paper cites Masked-attention mask transformer for universal image segmen- tation,.

A2Mamba: Attention-augmented State Space Models for Visual Recognition Masked-attention mask transformer for universal image segmen- tation,

Reference 75

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:09:51.335264Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 9ef877b5-f265-4913-af54-a63d0a1f6db3 · outbound

This paper cites Feedformer: Revisit- ing transformer decoder for efficient semantic segmentation,.

A2Mamba: Attention-augmented State Space Models for Visual Recognition Feedformer: Revisit- ing transformer decoder for efficient semantic segmentation,

Reference 76

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:09:51.314652Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 81f1c021-34b0-4468-925f-b4a2420c8612 · outbound

This paper cites Low-resolution self-attention for semantic segmentation,.

A2Mamba: Attention-augmented State Space Models for Visual Recognition Low-resolution self-attention for semantic segmentation,

Reference 77

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:09:51.296202Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation adba4fd6-f889-4c54-afb7-0d5615bf66d0 · outbound

This paper cites Understanding the effective receptive field in deep convolutional neural networks,.

A2Mamba: Attention-augmented State Space Models for Visual Recognition Understanding the effective receptive field in deep convolutional neural networks,

Reference 78

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:09:51.278942Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 412d77b3-d95a-4612-b64c-f1e21ae723f6 · outbound

This paper cites Deformable convnets v2: More deformable, better results,.

A2Mamba: Attention-augmented State Space Models for Visual Recognition Deformable convnets v2: More deformable, better results,

Reference 79

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:09:51.261083Z

Source-reported events for the cited work

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