Paper Citation Record · LEDGER

UNetVL: Enhancing 3D Medical Image Segmentation with Chebyshev KAN Powered Vision-LSTM

As of 20 August 2026, this Paper Citation Record lists 22 of 22 outbound references and 1 inbound Pith citation observation for arXiv:2501.07017.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2501.07017 v2

Coverage vector

measured 22 of 22 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T20:53:48.232877Z

measured 23 of 23 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-10T20:53:47.163086Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: pith, observed 2026-08-10T20:53:48.330102Z

Reference resolution

22 of 22 outbound references displayed

verified exact1
verified fuzzy11
unresolved10
parse uncertain0
malformed identifier0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation f5107103-e7ed-42d6-94c1-8554c578cd6f · outbound

This paper cites UNetVL: Enhancing 3D Medical Image Segmentation with Chebyshev KAN Powered Vision-LSTM.

UNetVL: Enhancing 3D Medical Image Segmentation with Chebyshev KAN Powered Vision-LSTM UNetVL: Enhancing 3D Medical Image Segmentation with Chebyshev KAN Powered Vision-LSTM

Reference 1

Resolution: verified exact; local_arxiv, observed 2026-08-10T20:53:48.373528Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 752dbf46-62b7-41f2-ab15-a7c75a1be8b1 · outbound

This paper cites Architecture Overview We present the overall architecture of our UNETVL model in Fig.

UNetVL: Enhancing 3D Medical Image Segmentation with Chebyshev KAN Powered Vision-LSTM Architecture Overview We present the overall architecture of our UNETVL model in Fig

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:53:49.204721Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 2b1b7490-2d43-4cf4-a5e5-c2a028bfb09a · outbound

This paper cites an unresolved cited work.

UNetVL: Enhancing 3D Medical Image Segmentation with Chebyshev KAN Powered Vision-LSTM Unresolved cited work

Reference 3

Resolution: unresolved; raw_fallback, observed 2026-08-10T20:53:49.153789Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 3f28bfeb-9552-46ae-840b-22ac9d1b4c12 · outbound

This paper cites As shown in Table 1, when comparing the performance of the ViL architecture with Chebyshev KAN to the UNETR baseline, a signifi- cant improvement is observed.

UNetVL: Enhancing 3D Medical Image Segmentation with Chebyshev KAN Powered Vision-LSTM As shown in Table 1, when comparing the performance of the ViL architecture with Chebyshev KAN to the UNETR baseline, a signifi- cant improvement is observed

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:53:49.135688Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 5f349a99-5402-49b6-8e5f-6c0fb844ea41 · outbound

This paper cites an unresolved cited work.

UNetVL: Enhancing 3D Medical Image Segmentation with Chebyshev KAN Powered Vision-LSTM Unresolved cited work

Reference 5

Resolution: unresolved; raw_fallback, observed 2026-08-10T20:53:49.002094Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 5c663d54-ff5a-4c00-ad31-75519f833a32 · outbound

This paper cites [6] and Ji et al.

UNetVL: Enhancing 3D Medical Image Segmentation with Chebyshev KAN Powered Vision-LSTM [6] and Ji et al

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:53:48.946085Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 27d249c6-f89e-4093-b2e5-34b474a0b3d6 · outbound

This paper cites Unetr: Transformers for 3d medical image segmentation,.

UNetVL: Enhancing 3D Medical Image Segmentation with Chebyshev KAN Powered Vision-LSTM Unetr: Transformers for 3d medical image segmentation,

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-10T20:53:47.465949Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7b37f776-ad8c-4abc-a303-72b9fca4bd09 · outbound

This paper cites U-net: Convolutional networks for biomedical im- age segmentation,.

UNetVL: Enhancing 3D Medical Image Segmentation with Chebyshev KAN Powered Vision-LSTM U-net: Convolutional networks for biomedical im- age segmentation,

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-10T20:53:47.752825Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 785d6d75-ce5f-4e08-8e0a-46fd10169b61 · outbound

This paper cites xLSTM: Extended Long Short-Term Memory.

UNetVL: Enhancing 3D Medical Image Segmentation with Chebyshev KAN Powered Vision-LSTM xLSTM: Extended Long Short-Term Memory

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-10T20:53:47.758173Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d3ede015-e191-41aa-a7ed-a251b906989c · outbound

This paper cites Vision-LSTM: xLSTM as Generic Vision Backbone.

UNetVL: Enhancing 3D Medical Image Segmentation with Chebyshev KAN Powered Vision-LSTM Vision-LSTM: xLSTM as Generic Vision Backbone

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-10T20:53:47.764682Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b83f39c2-94a3-41cc-9b14-5a9024516157 · outbound

This paper cites KAN: Kolmogorov-Arnold Networks.

UNetVL: Enhancing 3D Medical Image Segmentation with Chebyshev KAN Powered Vision-LSTM KAN: Kolmogorov-Arnold Networks

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-10T20:53:47.770455Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d931e120-fbe3-42f5-9fce-5bd5eecfbe8c · outbound

This paper cites Deep learning techniques for automatic mri cardiac multi-structures segmentation and diagnosis: is the problem solved?,.

UNetVL: Enhancing 3D Medical Image Segmentation with Chebyshev KAN Powered Vision-LSTM Deep learning techniques for automatic mri cardiac multi-structures segmentation and diagnosis: is the problem solved?,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:53:48.915428Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation c7f9dedd-f8c3-46da-a81f-a90d844ccc4b · outbound

This paper cites Amos: A large-scale abdominal multi-organ benchmark for versa- tile medical image segmentation,.

UNetVL: Enhancing 3D Medical Image Segmentation with Chebyshev KAN Powered Vision-LSTM Amos: A large-scale abdominal multi-organ benchmark for versa- tile medical image segmentation,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:53:48.780589Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 8aef2c01-07fa-4d78-afa2-a219d93d0e13 · outbound

This paper cites nnu-net revisited: A call for rig- orous validation in 3d medical image segmentation,.

UNetVL: Enhancing 3D Medical Image Segmentation with Chebyshev KAN Powered Vision-LSTM nnu-net revisited: A call for rig- orous validation in 3d medical image segmentation,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:53:48.765913Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation e44af1cd-4d98-4596-a771-6a61826a897b · outbound

This paper cites Chebyshev Polynomial-Based Kolmogorov-Arnold Networks: An Efficient Architecture for Nonlinear Function Approximation.

UNetVL: Enhancing 3D Medical Image Segmentation with Chebyshev KAN Powered Vision-LSTM Chebyshev Polynomial-Based Kolmogorov-Arnold Networks: An Efficient Architecture for Nonlinear Function Approximation

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-10T20:53:47.960521Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4f7d6c25-97de-4ee6-abc7-85966f3645e4 · outbound

This paper cites nnu-net: a self- configuring method for deep learning-based biomedical image segmentation,.

UNetVL: Enhancing 3D Medical Image Segmentation with Chebyshev KAN Powered Vision-LSTM nnu-net: a self- configuring method for deep learning-based biomedical image segmentation,

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-10T20:53:48.025120Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ebb4fc51-ebbb-4384-ba1c-25f53996adb5 · outbound

This paper cites Swin unetr: Swin transformers for semantic segmentation of brain tumors in mri images,.

UNetVL: Enhancing 3D Medical Image Segmentation with Chebyshev KAN Powered Vision-LSTM Swin unetr: Swin transformers for semantic segmentation of brain tumors in mri images,

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-10T20:53:48.030787Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bdc5e1ea-00f2-4e35-a2bd-0679bf974ec8 · outbound

This paper cites Swinunetr- v2: Stronger swin transformers with stagewise convo- lutions for 3d medical image segmentation,.

UNetVL: Enhancing 3D Medical Image Segmentation with Chebyshev KAN Powered Vision-LSTM Swinunetr- v2: Stronger swin transformers with stagewise convo- lutions for 3d medical image segmentation,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:53:48.731480Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 17821a0b-336d-4c0d-aacb-761ec2a1a669 · outbound

This paper cites nnformer: V olumetric medical image segmenta- tion via a 3d transformer,.

UNetVL: Enhancing 3D Medical Image Segmentation with Chebyshev KAN Powered Vision-LSTM nnformer: V olumetric medical image segmenta- tion via a 3d transformer,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:53:48.596152Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 16ec8fe9-94e6-48ee-afb8-057fbd0e735a · outbound

This paper cites Cotr: Efficiently bridging cnn and transformer for 3d medical image segmentation,.

UNetVL: Enhancing 3D Medical Image Segmentation with Chebyshev KAN Powered Vision-LSTM Cotr: Efficiently bridging cnn and transformer for 3d medical image segmentation,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:53:48.543303Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 4c691280-2560-453c-8eb7-0395e000f620 · outbound

This paper cites Sam3d: Segment any- thing model in volumetric medical images,.

UNetVL: Enhancing 3D Medical Image Segmentation with Chebyshev KAN Powered Vision-LSTM Sam3d: Segment any- thing model in volumetric medical images,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:53:48.441452Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation b0ebe475-ae71-4acf-83a5-ade38c8f3074 · outbound

This paper cites U-kan makes strong backbone for medical image seg- mentation and generation,.

UNetVL: Enhancing 3D Medical Image Segmentation with Chebyshev KAN Powered Vision-LSTM U-kan makes strong backbone for medical image seg- mentation and generation,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:53:48.390789Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Pith citing papers

Observation f5107103-e7ed-42d6-94c1-8554c578cd6f · inbound