Paper Citation Record · LEDGER

ProKAN: Progressive Stacking of Kolmogorov-Arnold Networks for Efficient Liver Segmentation

As of 19 August 2026, this Paper Citation Record lists 27 of 27 outbound references and 0 inbound Pith citation observations for arXiv:2412.19713.

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

pith.paper-citation-record.v1
2412.19713 v1

Coverage vector

measured 27 of 27 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T23:58:55.285247Z

measured 27 of 27 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

27 of 27 outbound references displayed

verified exact1
verified fuzzy23
unresolved3
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 87db36f4-c159-4282-8b90-b24b0eb7a1e5 · outbound

This paper cites A likelihood and local constraint level set model for liver tumor segmentation from ct volumes,.

ProKAN: Progressive Stacking of Kolmogorov-Arnold Networks for Efficient Liver Segmentation A likelihood and local constraint level set model for liver tumor segmentation from ct volumes,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:58:55.592497Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation bf3d7e1f-dc5d-4890-826c-9d689da2f3a0 · outbound

This paper cites Semi-automatic liver tumor segmentation with hidden markov measure field model and non-parametric distribution estimation,.

ProKAN: Progressive Stacking of Kolmogorov-Arnold Networks for Efficient Liver Segmentation Semi-automatic liver tumor segmentation with hidden markov measure field model and non-parametric distribution estimation,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:58:55.582261Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 408d0283-fa4c-43ff-8a03-026106b586c3 · outbound

This paper cites Interactive liver tumor segmentation from ct scans using support vector classification with watershed,.

ProKAN: Progressive Stacking of Kolmogorov-Arnold Networks for Efficient Liver Segmentation Interactive liver tumor segmentation from ct scans using support vector classification with watershed,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:58:55.571693Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation fda5ede1-27fd-4ee5-89a4-80bd2d94e78d · outbound

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

ProKAN: Progressive Stacking of Kolmogorov-Arnold Networks for Efficient Liver Segmentation U-net: Convolutional networks for biomedical image segmentation,

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-10T23:58:55.206003Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7239d0a4-3924-423c-821a-3d099250fd1a · outbound

This paper cites 3d u-net: Learning dense volumetric segmentation from sparse annota- tion,.

ProKAN: Progressive Stacking of Kolmogorov-Arnold Networks for Efficient Liver Segmentation 3d u-net: Learning dense volumetric segmentation from sparse annota- tion,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:58:55.554673Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 4f1403b3-03af-49cf-8b91-1dffe08f7efc · outbound

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

ProKAN: Progressive Stacking of Kolmogorov-Arnold Networks for Efficient Liver Segmentation Unet++: Redesigning skip connections to exploit multiscale features in image segmentation,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:58:55.544777Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 2a0cdb79-b60b-45a1-bd0e-e57aff409d35 · outbound

This paper cites Modified u- net (mu-net) with incorporation of object-dependent high level features for improved liver and liver-tumor segmentation in ct images,.

ProKAN: Progressive Stacking of Kolmogorov-Arnold Networks for Efficient Liver Segmentation Modified u- net (mu-net) with incorporation of object-dependent high level features for improved liver and liver-tumor segmentation in ct images,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:58:55.534123Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 909b359a-e098-4a6d-ac08-67dc6f83c9d5 · outbound

This paper cites H-denseunet: Hybrid densely connected unet for liver and tumor segmentation from ct volumes,.

ProKAN: Progressive Stacking of Kolmogorov-Arnold Networks for Efficient Liver Segmentation H-denseunet: Hybrid densely connected unet for liver and tumor segmentation from ct volumes,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:58:55.523140Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 5dc5768d-54f3-4b82-8624-e0ee556fd91e · outbound

This paper cites Bridging the gap between 2d and 3d contexts in ct volume for liver and tumor segmentation,.

ProKAN: Progressive Stacking of Kolmogorov-Arnold Networks for Efficient Liver Segmentation Bridging the gap between 2d and 3d contexts in ct volume for liver and tumor segmentation,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:58:55.512394Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 240d95db-4b64-460a-88bc-03f331d33869 · outbound

This paper cites Dlau: A scalable deep learning accelerator unit on fpga,.

ProKAN: Progressive Stacking of Kolmogorov-Arnold Networks for Efficient Liver Segmentation Dlau: A scalable deep learning accelerator unit on fpga,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:58:55.501108Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation aa0474b2-ac64-45c7-b897-8360c54faa26 · outbound

This paper cites Accommodating transformer onto fpga: Coupling the balanced model compression and fpga-implementation optimization,.

ProKAN: Progressive Stacking of Kolmogorov-Arnold Networks for Efficient Liver Segmentation Accommodating transformer onto fpga: Coupling the balanced model compression and fpga-implementation optimization,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:58:55.490417Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 36b21a0b-1151-4376-8a40-71e0e7823bd4 · outbound

This paper cites An fpga-based transformer accelerator using output block stationary dataflow for object recognition applications,.

ProKAN: Progressive Stacking of Kolmogorov-Arnold Networks for Efficient Liver Segmentation An fpga-based transformer accelerator using output block stationary dataflow for object recognition applications,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:58:55.479130Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation f80b80ac-dffc-4447-837b-0fc4d8878f56 · outbound

This paper cites Transpim: A memory- based acceleration via software-hardware co-design for transformer,.

ProKAN: Progressive Stacking of Kolmogorov-Arnold Networks for Efficient Liver Segmentation Transpim: A memory- based acceleration via software-hardware co-design for transformer,

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-10T23:58:55.237299Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 36c6eeec-3c13-44e1-b5f1-49e50f5682ce · outbound

This paper cites Thundernet: A turbo unified network for real-time semantic segmentation,.

ProKAN: Progressive Stacking of Kolmogorov-Arnold Networks for Efficient Liver Segmentation Thundernet: A turbo unified network for real-time semantic segmentation,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:58:55.461706Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 9e8478ee-bd04-472b-a6f6-b3cc121b78fc · outbound

This paper cites Implementation of fpga-based accelerator for deep neural networks,.

ProKAN: Progressive Stacking of Kolmogorov-Arnold Networks for Efficient Liver Segmentation Implementation of fpga-based accelerator for deep neural networks,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:58:55.450943Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 07ea5efa-c75e-4d23-b13e-871403e7c312 · outbound

This paper cites Optimizing the convolution operation to accelerate deep neural networks on fpga,.

ProKAN: Progressive Stacking of Kolmogorov-Arnold Networks for Efficient Liver Segmentation Optimizing the convolution operation to accelerate deep neural networks on fpga,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:58:55.440366Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 6cea9e75-6ac9-4c5b-942d-babda6f23d26 · outbound

This paper cites Light-weight hybrid convolutional network for liver tumor segmentation.

ProKAN: Progressive Stacking of Kolmogorov-Arnold Networks for Efficient Liver Segmentation Light-weight hybrid convolutional network for liver tumor segmentation

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:58:55.429551Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 40c77e2c-1da0-453e-b39a-7768e9711f70 · outbound

This paper cites Hybrid cascaded neural network for liver lesion segmentation,.

ProKAN: Progressive Stacking of Kolmogorov-Arnold Networks for Efficient Liver Segmentation Hybrid cascaded neural network for liver lesion segmentation,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:58:55.418664Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation b47ac29a-6505-44d7-af38-b446973e3067 · outbound

This paper cites Bridging the gap between 2d and 3d contexts in ct volume for liver and tumor segmentation,.

ProKAN: Progressive Stacking of Kolmogorov-Arnold Networks for Efficient Liver Segmentation Bridging the gap between 2d and 3d contexts in ct volume for liver and tumor segmentation,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:58:55.407754Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 6d859cdf-1a8d-434e-b85a-a5c91cdcce72 · outbound

This paper cites The liver tumor segmentation benchmark (lits),.

ProKAN: Progressive Stacking of Kolmogorov-Arnold Networks for Efficient Liver Segmentation The liver tumor segmentation benchmark (lits),

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:58:55.397368Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation a91d3721-d327-441a-84f7-ba350a735ceb · outbound

This paper cites Doubleu-net: A deep convolutional neural network for medical im- age segmentation,.

ProKAN: Progressive Stacking of Kolmogorov-Arnold Networks for Efficient Liver Segmentation Doubleu-net: A deep convolutional neural network for medical im- age segmentation,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:58:55.385901Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 943edc03-d21c-4225-a4a7-b99f033aeacc · outbound

This paper cites Real-time polyp detection, localization and segmentation in colonoscopy using deep learning,.

ProKAN: Progressive Stacking of Kolmogorov-Arnold Networks for Efficient Liver Segmentation Real-time polyp detection, localization and segmentation in colonoscopy using deep learning,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:58:55.375212Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 7f212d93-4ac9-485c-bfce-3c430b8708b6 · outbound

This paper cites ScribblePrompt: Fast and Flexible Interactive Segmentation for Any Biomedical Image.

ProKAN: Progressive Stacking of Kolmogorov-Arnold Networks for Efficient Liver Segmentation ScribblePrompt: Fast and Flexible Interactive Segmentation for Any Biomedical Image

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-10T23:58:55.271719Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 192cb6dd-4cc9-4ae7-9342-18ed06ff3f2e · outbound

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

ProKAN: Progressive Stacking of Kolmogorov-Arnold Networks for Efficient Liver Segmentation Unext: Mlp-based rapid medical image segmentation network,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:58:55.364379Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 095642a6-42ee-431d-bf32-c550db8e3ed0 · outbound

This paper cites On-the- fly test-time adaptation for medical image segmentation,.

ProKAN: Progressive Stacking of Kolmogorov-Arnold Networks for Efficient Liver Segmentation On-the- fly test-time adaptation for medical image segmentation,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:58:55.353921Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 2388a9b9-2463-4c29-ae6d-a9a4a0aa1c48 · outbound

This paper cites From denoising training to test-time adaptation: Enhancing domain generalization for medical image segmentation,.

ProKAN: Progressive Stacking of Kolmogorov-Arnold Networks for Efficient Liver Segmentation From denoising training to test-time adaptation: Enhancing domain generalization for medical image segmentation,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:58:55.343573Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 5f1826c9-c3a2-4395-bcef-89c1c3624b66 · outbound

This paper cites CT Liver Segmentation via PVT-based Encoding and Refined Decoding.

ProKAN: Progressive Stacking of Kolmogorov-Arnold Networks for Efficient Liver Segmentation CT Liver Segmentation via PVT-based Encoding and Refined Decoding

Reference 27

Resolution: verified exact; local_arxiv, observed 2026-08-10T23:58:55.320909Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Pith citing papers

No inbound Pith citation observations are available.