Paper Citation Record · LEDGER

GroupKAN: Efficient Kolmogorov-Arnold Networks via Grouped Spline Modeling

As of 4 August 2026, this Paper Citation Record lists 36 of 36 outbound references and 2 inbound Pith citation observations for arXiv:2511.05477.

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

pith.paper-citation-record.v1
2511.05477 v2

Coverage vector

measured 36 of 36 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-05-17T23:30:19.949106Z

measured 38 of 38 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-03T06:30:56.289259+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-02T09:24:30.394363Z

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

36 of 36 outbound references displayed

verified exact8
verified fuzzy27
unresolved1
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation f04d8245-18ec-41b2-a1e2-acba42ab94fe · outbound

This paper cites Medical image segmentation using deep learning: A survey.IET image processing, 16(5):1243–1267.

GroupKAN: Efficient Kolmogorov-Arnold Networks via Grouped Spline Modeling Medical image segmentation using deep learning: A survey.IET image processing, 16(5):1243–1267

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T23:30:30.092938Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 25fc10b5-a5d0-48fa-bca3-7346e323868b · outbound

This paper cites A review of medical image segmentation algorithms.EAI Endorsed Transactions on Pervasive Health & Technology, 7(27).

GroupKAN: Efficient Kolmogorov-Arnold Networks via Grouped Spline Modeling A review of medical image segmentation algorithms.EAI Endorsed Transactions on Pervasive Health & Technology, 7(27)

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T23:30:30.099741Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation ba1b654c-7265-40dd-93c5-5bb4c0ef2cee · outbound

This paper cites an unresolved cited work.

GroupKAN: Efficient Kolmogorov-Arnold Networks via Grouped Spline Modeling Unresolved cited work

Reference 3

Resolution: unresolved; raw_fallback, observed 2026-05-17T23:30:30.085721Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 1c384645-c19b-47ab-bf8c-bd66bdf1e467 · outbound

This paper cites Generalist medical foundation model improves prostate cancer segmentation from multimodal mri images.

GroupKAN: Efficient Kolmogorov-Arnold Networks via Grouped Spline Modeling Generalist medical foundation model improves prostate cancer segmentation from multimodal mri images

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T23:30:30.078872Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation a113735f-d258-4c04-b5d7-8274286e1aa9 · outbound

This paper cites Comprehensive review of recent developments in visual object detection based on deep learning.Artificial Intelligence Review, 58(9):277.

GroupKAN: Efficient Kolmogorov-Arnold Networks via Grouped Spline Modeling Comprehensive review of recent developments in visual object detection based on deep learning.Artificial Intelligence Review, 58(9):277

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T23:30:30.074851Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation a73f3b5f-7f64-4053-a6c2-74a5c257737d · outbound

This paper cites U-net: Convolutional networks for biomedical image segmentation.

GroupKAN: Efficient Kolmogorov-Arnold Networks via Grouped Spline Modeling U-net: Convolutional networks for biomedical image segmentation

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T23:30:30.082494Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 6f242a6c-4504-4ffd-97d0-b95e14c622b7 · outbound

This paper cites Efficient acceleration of deep learning inference on resource-constrained edge devices: A review.Proceedings of the IEEE, 111(1):42–91.

GroupKAN: Efficient Kolmogorov-Arnold Networks via Grouped Spline Modeling Efficient acceleration of deep learning inference on resource-constrained edge devices: A review.Proceedings of the IEEE, 111(1):42–91

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T23:30:30.089518Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 73614bc9-1ba5-4f52-b0a4-e1bfdf0981f1 · outbound

This paper cites A comprehensive survey of convolutions in deep learning: Applications, challenges, and future trends.IEEE Access, 12:41180–41218.

GroupKAN: Efficient Kolmogorov-Arnold Networks via Grouped Spline Modeling A comprehensive survey of convolutions in deep learning: Applications, challenges, and future trends.IEEE Access, 12:41180–41218

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T23:30:30.096378Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation ca947e97-7535-4629-9759-75022dcba484 · outbound

This paper cites Transformer quality in linear time.

GroupKAN: Efficient Kolmogorov-Arnold Networks via Grouped Spline Modeling Transformer quality in linear time

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T23:30:30.070841Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation ccd7af02-1b91-490c-810a-225bfc2b31ca · outbound

This paper cites A practical survey on faster and lighter transformers.

GroupKAN: Efficient Kolmogorov-Arnold Networks via Grouped Spline Modeling A practical survey on faster and lighter transformers

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T23:30:30.066946Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 2fc96ad5-8c9d-4d15-8c5e-2e1a5c46ec41 · outbound

This paper cites An attentive inductive bias for sequential recommendation beyond the self-attention.

GroupKAN: Efficient Kolmogorov-Arnold Networks via Grouped Spline Modeling An attentive inductive bias for sequential recommendation beyond the self-attention

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T23:30:30.062887Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 5fe8a10a-a98a-41d5-a36f-77a1d1637e66 · outbound

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

GroupKAN: Efficient Kolmogorov-Arnold Networks via Grouped Spline Modeling Mamba: Linear-Time Sequence Modeling with Selective State Spaces

Reference 12

Resolution: verified exact; local_arxiv, observed 2026-05-17T23:30:29.225503Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 46bd8819-c376-4440-840c-067fb028de2f · outbound

This paper cites U-kan makes strong backbone for medical image segmentation and generation.

GroupKAN: Efficient Kolmogorov-Arnold Networks via Grouped Spline Modeling U-kan makes strong backbone for medical image segmentation and generation

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T23:30:30.130237Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation c0d8850f-5f4c-4419-8639-7558b7421313 · outbound

This paper cites KAN: Kolmogorov-Arnold Networks.

GroupKAN: Efficient Kolmogorov-Arnold Networks via Grouped Spline Modeling KAN: Kolmogorov-Arnold Networks

Reference 14

Resolution: verified exact; local_arxiv, observed 2026-05-17T23:30:29.262406Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 2df297ca-9d98-4a17-a117-4d99718b87d0 · outbound

This paper cites Unet++: A nested u-net architecture for medical image segmentation.

GroupKAN: Efficient Kolmogorov-Arnold Networks via Grouped Spline Modeling Unet++: A nested u-net architecture for medical image segmentation

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T23:30:30.126782Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 030dd695-4864-4a25-8421-c535579eae5f · outbound

This paper cites Rethinking u-net: Task-adaptive mixture of skip connections for enhanced medical image segmentation.

GroupKAN: Efficient Kolmogorov-Arnold Networks via Grouped Spline Modeling Rethinking u-net: Task-adaptive mixture of skip connections for enhanced medical image segmentation

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T23:30:30.110269Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 5608af6a-bab8-4189-abce-943b3bee7e4e · outbound

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

GroupKAN: Efficient Kolmogorov-Arnold Networks via Grouped Spline Modeling Attention U-Net: Learning Where to Look for the Pancreas

Reference 17

Resolution: verified exact; local_arxiv, observed 2026-05-17T23:30:29.247677Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 20c2552a-5ec2-4eb8-9223-9d4acfa14384 · outbound

This paper cites nnwnet: Rethinking the use of transformers in biomedical image segmentation and calling for a unified evaluation benchmark.

GroupKAN: Efficient Kolmogorov-Arnold Networks via Grouped Spline Modeling nnwnet: Rethinking the use of transformers in biomedical image segmentation and calling for a unified evaluation benchmark

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T23:30:30.146187Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation de39097e-4a99-41b6-8657-a993a4439449 · outbound

This paper cites Smaformer: Synergistic multi-attention transformer for medical image segmentation.

GroupKAN: Efficient Kolmogorov-Arnold Networks via Grouped Spline Modeling Smaformer: Synergistic multi-attention transformer for medical image segmentation

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T23:30:30.153220Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 956184ff-193b-4dc1-8c31-164105483742 · outbound

This paper cites Unext: Mlp-based rapid medical image segmentation network.

GroupKAN: Efficient Kolmogorov-Arnold Networks via Grouped Spline Modeling Unext: Mlp-based rapid medical image segmentation network

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T23:30:30.120243Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 31ce0608-0f49-4b96-a80e-2a694058bf2b · outbound

This paper cites Rolling-unet: Revitalizing mlp’s ability to efficiently extract long-distance dependencies for medical image segmentation.

GroupKAN: Efficient Kolmogorov-Arnold Networks via Grouped Spline Modeling Rolling-unet: Revitalizing mlp’s ability to efficiently extract long-distance dependencies for medical image segmentation

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T23:30:30.106712Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 2417b644-4e78-4b70-b591-835ee7451c23 · outbound

This paper cites U-Mamba: Enhancing Long-range Dependency for Biomedical Image Segmentation.

GroupKAN: Efficient Kolmogorov-Arnold Networks via Grouped Spline Modeling U-Mamba: Enhancing Long-range Dependency for Biomedical Image Segmentation

Reference 22

Resolution: verified exact; local_arxiv, observed 2026-05-17T23:30:29.242728Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 70185073-0126-4e20-b35f-1dc21b79624d · outbound

This paper cites Convolutional Kolmogorov-Arnold Networks.

GroupKAN: Efficient Kolmogorov-Arnold Networks via Grouped Spline Modeling Convolutional Kolmogorov-Arnold Networks

Reference 23

Resolution: verified exact; arxiv_id, observed 2026-05-17T23:30:29.252870Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation ba7e28dc-16fc-4ab5-8a48-76f3080c959b · outbound

This paper cites Kolmogorov-Arnold Convolutions: Design Principles and Empirical Studies.

GroupKAN: Efficient Kolmogorov-Arnold Networks via Grouped Spline Modeling Kolmogorov-Arnold Convolutions: Design Principles and Empirical Studies

Reference 24

Resolution: verified exact; arxiv_id, observed 2026-05-17T23:30:29.258250Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation c5f7b259-daab-4036-b4e8-8b2794574e6c · outbound

This paper cites Rectified linear units improve restricted boltzmann machines.

GroupKAN: Efficient Kolmogorov-Arnold Networks via Grouped Spline Modeling Rectified linear units improve restricted boltzmann machines

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T23:30:30.143024Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 87897f9a-ea69-4f99-924b-7b6c6527ba49 · outbound

This paper cites Gaussian Error Linear Units (GELUs).

GroupKAN: Efficient Kolmogorov-Arnold Networks via Grouped Spline Modeling Gaussian Error Linear Units (GELUs)

Reference 26

Resolution: verified exact; local_arxiv, observed 2026-05-17T23:30:29.231349Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 340578ac-c96f-4eea-a488-1a09d08dc502 · outbound

This paper cites Telu activation function for fast and stable deep learning.

GroupKAN: Efficient Kolmogorov-Arnold Networks via Grouped Spline Modeling Telu activation function for fast and stable deep learning

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T23:30:30.149342Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 61c39491-9b38-499f-9182-569af3916503 · outbound

This paper cites Gompertz Linear Units: Leveraging Asymmetry for Enhanced Learning Dynamics.

GroupKAN: Efficient Kolmogorov-Arnold Networks via Grouped Spline Modeling Gompertz Linear Units: Leveraging Asymmetry for Enhanced Learning Dynamics

Reference 28

Resolution: verified exact; arxiv_id, observed 2026-05-17T23:30:29.237302Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation aa11f753-de5f-4e6b-ade3-da3da80c4b22 · outbound

This paper cites Cvt: Introducing convolutions to vision transformers.

GroupKAN: Efficient Kolmogorov-Arnold Networks via Grouped Spline Modeling Cvt: Introducing convolutions to vision transformers

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T23:30:30.136974Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 4da01b89-ea7c-409f-990c-4c87b46ddc86 · outbound

This paper cites Pvt v2: Improved baselines with pyramid vision transformer.Computational visual media, 8(3):415–424.

GroupKAN: Efficient Kolmogorov-Arnold Networks via Grouped Spline Modeling Pvt v2: Improved baselines with pyramid vision transformer.Computational visual media, 8(3):415–424

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T23:30:30.103226Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 71ba12d4-ccae-4f74-804d-7f3783098abe · outbound

This paper cites On the representations of continuous functions of many variables by super- position of continuous functions of one variable and addition.

GroupKAN: Efficient Kolmogorov-Arnold Networks via Grouped Spline Modeling On the representations of continuous functions of many variables by super- position of continuous functions of one variable and addition

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T23:30:30.116864Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 4b7d5060-fc83-4e10-bbc3-aff36229542b · outbound

This paper cites Dataset of breast ultrasound images.

GroupKAN: Efficient Kolmogorov-Arnold Networks via Grouped Spline Modeling Dataset of breast ultrasound images

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T23:30:30.139966Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 4e9f379b-5ec0-431d-95e2-29f11cdc0e0e · outbound

This paper cites Gland segmentation in colon histology images: The glas challenge contest.Medical image analysis, 35:489–502.

GroupKAN: Efficient Kolmogorov-Arnold Networks via Grouped Spline Modeling Gland segmentation in colon histology images: The glas challenge contest.Medical image analysis, 35:489–502

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T23:30:30.156905Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation fad437a8-b039-426f-82ae-cc5fe8d084c7 · outbound

This paper cites Wm-dova maps for accurate polyp highlighting in colonoscopy: Validation vs.

GroupKAN: Efficient Kolmogorov-Arnold Networks via Grouped Spline Modeling Wm-dova maps for accurate polyp highlighting in colonoscopy: Validation vs

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T23:30:30.133456Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 694dad08-46b0-43e8-b2e9-6b92cfb888ee · outbound

This paper cites Individual comparisons by ranking methods.

GroupKAN: Efficient Kolmogorov-Arnold Networks via Grouped Spline Modeling Individual comparisons by ranking methods

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T23:30:30.123519Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 39eba616-ba55-426c-8ac1-faa12bb7046c · outbound

This paper cites Transformers without normalization.

GroupKAN: Efficient Kolmogorov-Arnold Networks via Grouped Spline Modeling Transformers without normalization

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T23:30:30.113541Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Pith citing papers

Observation d20a9d44-aec0-40d1-810e-e832da5197ad · inbound

SechKAN: Kolmogorov-Arnold Networks with Hyperbolic Secant Functions cites this paper.

SechKAN: Kolmogorov-Arnold Networks with Hyperbolic Secant Functions GroupKAN: Efficient Kolmogorov-Arnold Networks via Grouped Spline Modeling

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-02T09:24:30.394363Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d7add48f-c063-4bf8-96f5-ca5235914327 · inbound

KANEx: Translating Kolmogorov-Arnold Networks' Interpretability to Medical Explainability cites this paper.

KANEx: Translating Kolmogorov-Arnold Networks' Interpretability to Medical Explainability GroupKAN: Efficient Kolmogorov-Arnold Networks via Grouped Spline Modeling

Reference 13

Resolution: unresolved; no resolver link, observed 2026-07-31T06:40:23.853194Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.