Med-URWKV{\dag}: Toward Enhanced Pretrained Pure VRWKV Models for Medical Image Segmentation | Paper Citation Record

Observation 3749c2c2-9ba4-463d-a581-ed5f45afa2d3 · outbound

This paper cites Dataset of breast ultrasound images.

Med-URWKV{\dag}: Toward Enhanced Pretrained Pure VRWKV Models for Medical Image Segmentation Dataset of breast ultrasound images

Reference 1

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Observation bcbd9bba-716b-4f29-9c85-7f49e0002395 · outbound

This paper cites 3D Densely Convolutional Networks for Volumetric Segmentation.

Med-URWKV{\dag}: Toward Enhanced Pretrained Pure VRWKV Models for Medical Image Segmentation 3D Densely Convolutional Networks for Volumetric Segmentation

Reference 2

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Observation 55f698a0-0240-4057-b384-ea6f9245631b · outbound

This paper cites Swin-unet: Unet-like pure transformer for medical image segmentation,in:Europeanconferenceoncomputervision,Springer.

Med-URWKV{\dag}: Toward Enhanced Pretrained Pure VRWKV Models for Medical Image Segmentation Swin-unet: Unet-like pure transformer for medical image segmentation,in:Europeanconferenceoncomputervision,Springer

Reference 3

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This paper cites Aau-net: an adaptive attention u-net for breast lesions segmentation in ultrasound images.

Med-URWKV{\dag}: Toward Enhanced Pretrained Pure VRWKV Models for Medical Image Segmentation Aau-net: an adaptive attention u-net for breast lesions segmentation in ultrasound images

Reference 5

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Observation f0711ea7-f971-44c2-9da6-eb0a2bb7fe91 · outbound

This paper cites TransUNet: Transformers Make Strong Encoders for Medical Image Segmentation.

Med-URWKV{\dag}: Toward Enhanced Pretrained Pure VRWKV Models for Medical Image Segmentation TransUNet: Transformers Make Strong Encoders for Medical Image Segmentation

Reference 6

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This paper cites Zig-rir: Zigzag rwkv-in-rwkv for efficient medicalimagesegmentation.

Med-URWKV{\dag}: Toward Enhanced Pretrained Pure VRWKV Models for Medical Image Segmentation Zig-rir: Zigzag rwkv-in-rwkv for efficient medicalimagesegmentation

Reference 7

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Reference 8

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Med-URWKV{\dag}: Toward Enhanced Pretrained Pure VRWKV Models for Medical Image Segmentation Unresolved cited work

Reference 9

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Observation d3a7bc74-3863-42e7-9c8a-13909be82772 · outbound

This paper cites Imagenet: A large-scale hierarchical image database, in: 2009 IEEE conferenceoncomputervisionandpatternrecognition,Ieee.pp.248– 255.

Med-URWKV{\dag}: Toward Enhanced Pretrained Pure VRWKV Models for Medical Image Segmentation Imagenet: A large-scale hierarchical image database, in: 2009 IEEE conferenceoncomputervisionandpatternrecognition,Ieee.pp.248– 255

Reference 10

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Observation d3163082-ec72-415a-b1ec-9bcce90a78f7 · outbound

This paper cites An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale.

Med-URWKV{\dag}: Toward Enhanced Pretrained Pure VRWKV Models for Medical Image Segmentation An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Reference 11

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Observation 54af001e-4564-471e-97eb-5dfbeee93f44 · outbound

This paper cites Vision-RWKV: Efficient and Scalable Visual Perception with RWKV-Like Architectures.

Med-URWKV{\dag}: Toward Enhanced Pretrained Pure VRWKV Models for Medical Image Segmentation Vision-RWKV: Efficient and Scalable Visual Perception with RWKV-Like Architectures

Reference 12

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This paper cites Y-net: A spatiospectral dual-encoder network for medical image segmenta- tion, in: International conference on medical image computing and computer-assisted intervention, Springer.

Med-URWKV{\dag}: Toward Enhanced Pretrained Pure VRWKV Models for Medical Image Segmentation Y-net: A spatiospectral dual-encoder network for medical image segmenta- tion, in: International conference on medical image computing and computer-assisted intervention, Springer

Reference 13

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Observation 21716399-fdbe-454b-b0a2-f580fc26d9a7 · outbound

This paper cites Feature extraction technique using discrete wavelet transform for image classification, in: 2007 5th Student Conference on Research and Development, IEEE.

Med-URWKV{\dag}: Toward Enhanced Pretrained Pure VRWKV Models for Medical Image Segmentation Feature extraction technique using discrete wavelet transform for image classification, in: 2007 5th Student Conference on Research and Development, IEEE

Reference 14

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This paper cites an unresolved cited work.

Med-URWKV{\dag}: Toward Enhanced Pretrained Pure VRWKV Models for Medical Image Segmentation Unresolved cited work

Reference 15

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Observation 607fe9c3-8869-4e2a-b7cb-0d3d31fe3d37 · outbound

This paper cites Mamba: Linear-Time Sequence Modeling with Selective State Spaces.

Med-URWKV{\dag}: Toward Enhanced Pretrained Pure VRWKV Models for Medical Image Segmentation Mamba: Linear-Time Sequence Modeling with Selective State Spaces

Reference 16

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This paper cites Unetr: Transformers for 3d medicalimagesegmentation,in:ProceedingsoftheIEEE/CVFwinter conference on applications of computer vision, pp.

Med-URWKV{\dag}: Toward Enhanced Pretrained Pure VRWKV Models for Medical Image Segmentation Unetr: Transformers for 3d medicalimagesegmentation,in:ProceedingsoftheIEEE/CVFwinter conference on applications of computer vision, pp

Reference 17

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Med-URWKV{\dag}: Toward Enhanced Pretrained Pure VRWKV Models for Medical Image Segmentation Unresolved cited work

Reference 18

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Observation 772a142f-38c5-436d-9cb5-2885f6467c6a · outbound

This paper cites Progressive multiscale consistent network for multiclass fundus lesion segmenta- tion.

Med-URWKV{\dag}: Toward Enhanced Pretrained Pure VRWKV Models for Medical Image Segmentation Progressive multiscale consistent network for multiclass fundus lesion segmenta- tion

Reference 19

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Observation ea915a19-3e18-43b2-a800-d2cf56dd3bdf · outbound

This paper cites H2former:An efficienthierarchicalhybridtransformerformedicalimagesegmenta- tion.

Med-URWKV{\dag}: Toward Enhanced Pretrained Pure VRWKV Models for Medical Image Segmentation H2former:An efficienthierarchicalhybridtransformerformedicalimagesegmenta- tion

Reference 20

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Med-URWKV{\dag}: Toward Enhanced Pretrained Pure VRWKV Models for Medical Image Segmentation Unresolved cited work

Reference 21

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This paper cites Wavelet-assisted multi-frequency attention network for pansharpen- ing, in: Proceedings of the AAAI Conference on Artificial Intelli- gence, pp.

Med-URWKV{\dag}: Toward Enhanced Pretrained Pure VRWKV Models for Medical Image Segmentation Wavelet-assisted multi-frequency attention network for pansharpen- ing, in: Proceedings of the AAAI Conference on Artificial Intelli- gence, pp

Reference 22

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Observation 69e05224-4d5c-4f50-874c-3ea1a5e6741c · outbound

This paper cites MISSFormer: An Effective Medical Image Segmentation Transformer.

Med-URWKV{\dag}: Toward Enhanced Pretrained Pure VRWKV Models for Medical Image Segmentation MISSFormer: An Effective Medical Image Segmentation Transformer

Reference 23

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This paper cites Polyp2former: Boundary guided network based on transformer for polyp segmentation, in: 2023 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), IEEE.

Med-URWKV{\dag}: Toward Enhanced Pretrained Pure VRWKV Models for Medical Image Segmentation Polyp2former: Boundary guided network based on transformer for polyp segmentation, in: 2023 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), IEEE

Reference 24

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This paper cites Acc-unet: A completely convolutional unet model for the 2020s, in: International conference on medical image computing and computer-assisted intervention, Springer.

Med-URWKV{\dag}: Toward Enhanced Pretrained Pure VRWKV Models for Medical Image Segmentation Acc-unet: A completely convolutional unet model for the 2020s, in: International conference on medical image computing and computer-assisted intervention, Springer

Reference 25

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Observation 96e835e2-203a-4b78-b4ef-c6eab80855c9 · outbound

This paper cites Kvasir-seg: A segmented polyp dataset, in: International conference on multimedia modeling, Springer.

Med-URWKV{\dag}: Toward Enhanced Pretrained Pure VRWKV Models for Medical Image Segmentation Kvasir-seg: A segmented polyp dataset, in: International conference on multimedia modeling, Springer

Reference 26

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Observation 114ef992-5fd7-4463-95b0-4c048f2fa8d8 · outbound

This paper cites Rwkv-unet: Improving unet with long-range cooperationforeffectivemedicalimagesegmentation.

Med-URWKV{\dag}: Toward Enhanced Pretrained Pure VRWKV Models for Medical Image Segmentation Rwkv-unet: Improving unet with long-range cooperationforeffectivemedicalimagesegmentation

Reference 27

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This paper cites Mixunet: Mix the 2d and 3d models for robust medical image segmentation, in: 2023 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), IEEE.

Med-URWKV{\dag}: Toward Enhanced Pretrained Pure VRWKV Models for Medical Image Segmentation Mixunet: Mix the 2d and 3d models for robust medical image segmentation, in: 2023 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), IEEE

Reference 28

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This paper cites H-denseunet: hybrid densely connected unet for liver and tumor segmentationfromctvolumes.IEEEtransactionsonmedicalimaging 37, 2663–2674.

Med-URWKV{\dag}: Toward Enhanced Pretrained Pure VRWKV Models for Medical Image Segmentation H-denseunet: hybrid densely connected unet for liver and tumor segmentationfromctvolumes.IEEEtransactionsonmedicalimaging 37, 2663–2674

Reference 29

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This paper cites Can: Context-assisted full attention network for brain tissue segmentation.

Med-URWKV{\dag}: Toward Enhanced Pretrained Pure VRWKV Models for Medical Image Segmentation Can: Context-assisted full attention network for brain tissue segmentation

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:19:51.572882Z

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Observation 85493ec5-b32e-49e0-83b8-b1f9449f0f67 · outbound

This paper cites LightM-UNet: Mamba Assists in Lightweight UNet for Medical Image Segmentation.

Med-URWKV{\dag}: Toward Enhanced Pretrained Pure VRWKV Models for Medical Image Segmentation LightM-UNet: Mamba Assists in Lightweight UNet for Medical Image Segmentation

Reference 31

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Observation 6cbe24e2-7f5f-4767-9066-d8b4b5e04b76 · outbound

This paper cites IEEE Transactions on Medical Imaging.

Med-URWKV{\dag}: Toward Enhanced Pretrained Pure VRWKV Models for Medical Image Segmentation IEEE Transactions on Medical Imaging

Reference 32

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This paper cites Vmamba: Visual state space model.

Med-URWKV{\dag}: Toward Enhanced Pretrained Pure VRWKV Models for Medical Image Segmentation Vmamba: Visual state space model

Reference 33

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This paper cites V-net: Fully convolu- tional neural networks for volumetric medical image segmentation, in: 2016 fourth international conference on 3D vision (3DV), Ieee.

Med-URWKV{\dag}: Toward Enhanced Pretrained Pure VRWKV Models for Medical Image Segmentation V-net: Fully convolu- tional neural networks for volumetric medical image segmentation, in: 2016 fourth international conference on 3D vision (3DV), Ieee

Reference 34

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Med-URWKV{\dag}: Toward Enhanced Pretrained Pure VRWKV Models for Medical Image Segmentation Unresolved cited work

Reference 35

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Med-URWKV{\dag}: Toward Enhanced Pretrained Pure VRWKV Models for Medical Image Segmentation Unresolved cited work

Reference 36

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Med-URWKV{\dag}: Toward Enhanced Pretrained Pure VRWKV Models for Medical Image Segmentation Unresolved cited work

Reference 37

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Med-URWKV{\dag}: Toward Enhanced Pretrained Pure VRWKV Models for Medical Image Segmentation Unresolved cited work

Reference 38

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Observation e066f4b4-4ff6-48b2-826f-a88bf9cdbeb8 · outbound

This paper cites Attention U-Net: Learning Where to Look for the Pancreas.

Med-URWKV{\dag}: Toward Enhanced Pretrained Pure VRWKV Models for Medical Image Segmentation Attention U-Net: Learning Where to Look for the Pancreas

Reference 39

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This paper cites VM-UNet: Vision Mamba UNet for Medical Image Segmentation.

Med-URWKV{\dag}: Toward Enhanced Pretrained Pure VRWKV Models for Medical Image Segmentation VM-UNet: Vision Mamba UNet for Medical Image Segmentation

Reference 40

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Med-URWKV{\dag}: Toward Enhanced Pretrained Pure VRWKV Models for Medical Image Segmentation Unresolved cited work

Reference 41

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This paper cites Unext: Mlp-based rapid medical image segmentation network, in: International conference on medical image computing and computer-assisted intervention, Springer.

Med-URWKV{\dag}: Toward Enhanced Pretrained Pure VRWKV Models for Medical Image Segmentation Unext: Mlp-based rapid medical image segmentation network, in: International conference on medical image computing and computer-assisted intervention, Springer

Reference 42

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This paper cites Attention is all you need.

Med-URWKV{\dag}: Toward Enhanced Pretrained Pure VRWKV Models for Medical Image Segmentation Attention is all you need

Reference 43

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This paper cites Uctransnet:rethink- ing the skip connections in u-net from a channel-wise perspective withtransformer,in:ProceedingsoftheAAAIconferenceonartificial intelligence, pp.

Med-URWKV{\dag}: Toward Enhanced Pretrained Pure VRWKV Models for Medical Image Segmentation Uctransnet:rethink- ing the skip connections in u-net from a channel-wise perspective withtransformer,in:ProceedingsoftheAAAIconferenceonartificial intelligence, pp

Reference 44

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Observation acc7d437-50de-43bf-96a7-dc60b6e69eb3 · outbound

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Med-URWKV{\dag}: Toward Enhanced Pretrained Pure VRWKV Models for Medical Image Segmentation Unresolved cited work

Reference 45

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This paper cites Large window-based mamba unet for medical image segmentation: Beyond convolution and self-attention.

Med-URWKV{\dag}: Toward Enhanced Pretrained Pure VRWKV Models for Medical Image Segmentation Large window-based mamba unet for medical image segmentation: Beyond convolution and self-attention

Reference 46

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Observation 1349919c-f2dd-4f64-9ec4-7fc78e5fdff7 · outbound

This paper cites Set: Superpixel embedded transformer for skin lesion segmentation.

Med-URWKV{\dag}: Toward Enhanced Pretrained Pure VRWKV Models for Medical Image Segmentation Set: Superpixel embedded transformer for skin lesion segmentation

Reference 47

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This paper cites H-vmunet: High-order Vision Mamba UNet for Medical Image Segmentation.

Med-URWKV{\dag}: Toward Enhanced Pretrained Pure VRWKV Models for Medical Image Segmentation H-vmunet: High-order Vision Mamba UNet for Medical Image Segmentation

Reference 48

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This paper cites Mgfuseseg: Attention-guidedmulti-granularityfusionformedicalimagesegmen- tation,in:2023IEEEInternationalConferenceonBioinformaticsand Biomedicine (BIBM), IEEE.

Med-URWKV{\dag}: Toward Enhanced Pretrained Pure VRWKV Models for Medical Image Segmentation Mgfuseseg: Attention-guidedmulti-granularityfusionformedicalimagesegmen- tation,in:2023IEEEInternationalConferenceonBioinformaticsand Biomedicine (BIBM), IEEE

Reference 49

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Observation 7e13c9e4-6cba-4bee-8a30-13977a1ff0d0 · outbound

This paper cites Smnet: A semantic guided mamba network for remote sensing change detec- tion.

Med-URWKV{\dag}: Toward Enhanced Pretrained Pure VRWKV Models for Medical Image Segmentation Smnet: A semantic guided mamba network for remote sensing change detec- tion

Reference 50

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Observation a2c9e64d-fe33-413d-ac76-ca1aeb75b923 · outbound

This paper cites Urwkv: Unified rwkv model with multi-state perspective for low-light image restoration, in: Proceedings of the Computer Vision and Pattern Recognition Conference, pp.

Med-URWKV{\dag}: Toward Enhanced Pretrained Pure VRWKV Models for Medical Image Segmentation Urwkv: Unified rwkv model with multi-state perspective for low-light image restoration, in: Proceedings of the Computer Vision and Pattern Recognition Conference, pp

Reference 51

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Observation 27ed9b6c-2b8b-46ee-a3d6-268d108c01b0 · outbound

This paper cites FEAT: Full-Dimensional Efficient Attention Transformer for Medical Video Generation.

Med-URWKV{\dag}: Toward Enhanced Pretrained Pure VRWKV Models for Medical Image Segmentation FEAT: Full-Dimensional Efficient Attention Transformer for Medical Video Generation

Reference 52

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Observation c701cec7-dde3-483d-8680-c80fa110a05f · outbound

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Reference 53

Resolution: unresolved; raw_fallback, observed 2026-08-07T04:19:51.352971Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 1f8464e2-a8ce-4dea-be75-4ad1350949b0 · outbound

This paper cites An Attention Free Transformer.

Med-URWKV{\dag}: Toward Enhanced Pretrained Pure VRWKV Models for Medical Image Segmentation An Attention Free Transformer

Reference 54

Resolution: unresolved; no resolver link, observed 2026-08-07T04:19:50.652342Z

Source-reported events for the cited work

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Observation 2cbd6bc2-8d9f-4b8c-a6da-601e66e1b286 · outbound

This paper cites Out-of-distribution semantic occupancy prediction.

Med-URWKV{\dag}: Toward Enhanced Pretrained Pure VRWKV Models for Medical Image Segmentation Out-of-distribution semantic occupancy prediction

Reference 55

Resolution: unresolved; no resolver link, observed 2026-08-07T04:19:50.655638Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 767af4dc-a535-4d27-b6df-2a6d6ff6763d · outbound

This paper cites Smaformer: Synergistic multi-attention transformer for medicalimagesegmentation,in:2024IEEEInternationalConference onBioinformaticsandBiomedicine(BIBM),pp.4048–4053.

Med-URWKV{\dag}: Toward Enhanced Pretrained Pure VRWKV Models for Medical Image Segmentation Smaformer: Synergistic multi-attention transformer for medicalimagesegmentation,in:2024IEEEInternationalConference onBioinformaticsandBiomedicine(BIBM),pp.4048–4053

Reference 56

Resolution: unresolved; no resolver link, observed 2026-08-07T04:19:50.658935Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c2633a55-b638-42b0-93a9-c2f3c4a7e666 · outbound

This paper cites Bsbp-rwkv: Background suppression with boundary preservation for efficient medical image segmentation, in: Proceedingsofthe32ndACMInternationalConferenceonMultime- dia, pp.

Med-URWKV{\dag}: Toward Enhanced Pretrained Pure VRWKV Models for Medical Image Segmentation Bsbp-rwkv: Background suppression with boundary preservation for efficient medical image segmentation, in: Proceedingsofthe32ndACMInternationalConferenceonMultime- dia, pp

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:19:51.340640Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 7089423f-a886-4a1e-b915-f954eda7e005 · outbound

This paper cites an unresolved cited work.

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Reference 58

Resolution: unresolved; raw_fallback, observed 2026-08-07T04:19:51.327716Z

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 97c68aab-efbe-44a9-afe2-5d866cb337e4 · outbound

This paper cites an unresolved cited work.

Med-URWKV{\dag}: Toward Enhanced Pretrained Pure VRWKV Models for Medical Image Segmentation Unresolved cited work

Reference 59

Resolution: unresolved; raw_fallback, observed 2026-08-07T04:19:51.367045Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation bcad3903-b2da-4cf2-a084-eca3d76c5d08 · outbound

This paper cites Unet++: Redesigning skip connections to exploit multiscale features in image segmentation.

Med-URWKV{\dag}: Toward Enhanced Pretrained Pure VRWKV Models for Medical Image Segmentation Unet++: Redesigning skip connections to exploit multiscale features in image segmentation

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:19:51.302914Z

Source-reported events for the cited work

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Observation 37d72b86-6c4b-4f01-9a33-c789a8a408f3 · outbound

This paper cites Mamba or RWKV: Exploring High-Quality and High-Efficiency Segment Anything Model.

Med-URWKV{\dag}: Toward Enhanced Pretrained Pure VRWKV Models for Medical Image Segmentation Mamba or RWKV: Exploring High-Quality and High-Efficiency Segment Anything Model

Reference 61

Resolution: unresolved; no resolver link, observed 2026-08-07T04:19:50.648828Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ce5c3367-b811-44d3-a934-0c63a927b673 · outbound

This paper cites Spatial- frequency dual domain attention network for medical image segmen- tation,in:2024IEEEInternationalConferenceonBioinformaticsand Biomedicine (BIBM), IEEE.

Med-URWKV{\dag}: Toward Enhanced Pretrained Pure VRWKV Models for Medical Image Segmentation Spatial- frequency dual domain attention network for medical image segmen- tation,in:2024IEEEInternationalConferenceonBioinformaticsand Biomedicine (BIBM), IEEE

Reference 67

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:19:51.315063Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation e5fe99f8-f9b0-4823-9093-c121cdec1324 · outbound

This paper cites Personalizable long- context symbolic music infilling with midi-rwkv.

Med-URWKV{\dag}: Toward Enhanced Pretrained Pure VRWKV Models for Medical Image Segmentation Personalizable long- context symbolic music infilling with midi-rwkv

Reference 69

Resolution: unresolved; no resolver link, observed 2026-08-07T04:19:50.675085Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a2c1bd9c-24e3-4227-9b64-5e2c4a170fbb · outbound

This paper cites an unresolved cited work.

Med-URWKV{\dag}: Toward Enhanced Pretrained Pure VRWKV Models for Medical Image Segmentation Unresolved cited work

Reference 2016

Resolution: unresolved; no resolver link, observed 2026-08-07T04:19:47.638560Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e81feb45-2001-491f-8f10-d81acc69def2 · outbound

This paper cites Medical image analysis 35, 489–502.

Med-URWKV{\dag}: Toward Enhanced Pretrained Pure VRWKV Models for Medical Image Segmentation Medical image analysis 35, 489–502

Reference 2017

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:19:51.463069Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 97fd0a22-3000-45d3-81fd-4b95d4877cb6 · outbound

This paper cites an unresolved cited work.

Med-URWKV{\dag}: Toward Enhanced Pretrained Pure VRWKV Models for Medical Image Segmentation Unresolved cited work

Reference 2018

Resolution: unresolved; raw_fallback, observed 2026-08-07T04:19:51.778125Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 7047b697-e9ff-4e02-91e6-e1f157b573be · outbound

This paper cites RWKV: Reinventing RNNs for the Transformer Era.

Med-URWKV{\dag}: Toward Enhanced Pretrained Pure VRWKV Models for Medical Image Segmentation RWKV: Reinventing RNNs for the Transformer Era

Reference 2023

Resolution: unresolved; no resolver link, observed 2026-08-07T04:19:49.892673Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9c8a8680-6494-454f-b88b-e33bfba78891 · outbound

This paper cites 4261–4268.

Med-URWKV{\dag}: Toward Enhanced Pretrained Pure VRWKV Models for Medical Image Segmentation 4261–4268

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-07T04:19:50.316298Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4d167c54-c9f2-4434-9a00-d43b716cc2c7 · outbound

This paper cites an unresolved cited work.

Med-URWKV{\dag}: Toward Enhanced Pretrained Pure VRWKV Models for Medical Image Segmentation Unresolved cited work

Reference 2025

Resolution: unresolved; raw_fallback, observed 2026-08-07T04:19:51.717726Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Outbound references

Pith citing papers