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Paper Citation Record · LEDGER

Large Language Model Evaluated Stand-alone Attention-Assisted Graph Neural Network with Spatial and Structural Information Interaction for Precise Endoscopic Image Segmentation

As of 16 August 2026, this Paper Citation Record lists 34 of 34 outbound references and 0 inbound Pith citation observations for arXiv:2508.07028.

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

pith.paper-citation-record.v1
2508.07028 v1

Coverage vector

measured 34 of 34 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-05T22:26:53.242434Z

measured 34 of 34 standing notices

One-hop event checks from named stored sources.

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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

34 of 34 outbound references displayed

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External citation measurements

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Outbound references

Observation 2bfe4f72-f784-4782-92aa-404e8160675c · outbound

This paper cites Colorec- tal cancer: a review.

Large Language Model Evaluated Stand-alone Attention-Assisted Graph Neural Network with Spatial and Structural Information Interaction for Precise Endoscopic Image Segmentation Colorec- tal cancer: a review

Reference 1

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Observation 003c35d2-2636-4f2c-9fa1-599571b3aa36 · outbound

This paper cites Biomarkers for early detection of colorectal cancer and polyps: systematic review.

Large Language Model Evaluated Stand-alone Attention-Assisted Graph Neural Network with Spatial and Structural Information Interaction for Precise Endoscopic Image Segmentation Biomarkers for early detection of colorectal cancer and polyps: systematic review

Reference 2

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Observation 12c18330-de30-47dc-b4b2-e72155a4884e · outbound

This paper cites Deep dual- domain united guiding learning with global–local transformer-convolution u-net for ldct reconstruction.

Large Language Model Evaluated Stand-alone Attention-Assisted Graph Neural Network with Spatial and Structural Information Interaction for Precise Endoscopic Image Segmentation Deep dual- domain united guiding learning with global–local transformer-convolution u-net for ldct reconstruction

Reference 4

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Observation 98feb9fe-c324-469f-9ab5-3081a2dbc0f5 · outbound

This paper cites Lo- 8 mae: simple streamlined low-level masked autoen- coders for robust, generalized, and interpretable low- dose ct denoising.

Large Language Model Evaluated Stand-alone Attention-Assisted Graph Neural Network with Spatial and Structural Information Interaction for Precise Endoscopic Image Segmentation Lo- 8 mae: simple streamlined low-level masked autoen- coders for robust, generalized, and interpretable low- dose ct denoising

Reference 5

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Observation 07badff2-89ac-4304-a0b8-edbe1920d7bd · outbound

This paper cites Physics-informed score-based diffu- sion model for limited-angle reconstruction of cardiac computed tomography.

Large Language Model Evaluated Stand-alone Attention-Assisted Graph Neural Network with Spatial and Structural Information Interaction for Precise Endoscopic Image Segmentation Physics-informed score-based diffu- sion model for limited-angle reconstruction of cardiac computed tomography

Reference 6

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Observation 408228ee-c4b8-4449-88bd-6905e1ba5b1a · outbound

This paper cites Enhancing pathogen identification in cheese with high background microflora using an artificial neural network-enabled paper chromogenic array sen- sor approach.

Large Language Model Evaluated Stand-alone Attention-Assisted Graph Neural Network with Spatial and Structural Information Interaction for Precise Endoscopic Image Segmentation Enhancing pathogen identification in cheese with high background microflora using an artificial neural network-enabled paper chromogenic array sen- sor approach

Reference 7

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Observation 04fddf2e-8167-4d39-b09b-c848a2f5e3bc · outbound

This paper cites Patch- based dual-domain photon-counting ct data correction with residual-based wgan-vit.

Large Language Model Evaluated Stand-alone Attention-Assisted Graph Neural Network with Spatial and Structural Information Interaction for Precise Endoscopic Image Segmentation Patch- based dual-domain photon-counting ct data correction with residual-based wgan-vit

Reference 8

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Observation 547d5cb8-923f-4fe6-b5f7-d71915e40cdc · outbound

This paper cites Pranet: Parallel reverse attention network for polyp segmenta- tion.

Large Language Model Evaluated Stand-alone Attention-Assisted Graph Neural Network with Spatial and Structural Information Interaction for Precise Endoscopic Image Segmentation Pranet: Parallel reverse attention network for polyp segmenta- tion

Reference 9

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Observation 5fb67421-4c16-4530-88f7-f8656f30b0fc · outbound

This paper cites Acsnet: Action-context separation network for weakly super- vised temporal action localization.

Large Language Model Evaluated Stand-alone Attention-Assisted Graph Neural Network with Spatial and Structural Information Interaction for Precise Endoscopic Image Segmentation Acsnet: Action-context separation network for weakly super- vised temporal action localization

Reference 10

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Observation 064b4828-5e47-489a-9fac-bc2828873a9f · outbound

This paper cites An embedding-unleashing video polyp segmentation framework via region linking and scale alignment.

Large Language Model Evaluated Stand-alone Attention-Assisted Graph Neural Network with Spatial and Structural Information Interaction for Precise Endoscopic Image Segmentation An embedding-unleashing video polyp segmentation framework via region linking and scale alignment

Reference 11

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Observation aaf6bfe0-0e77-46c0-ae80-3b68164b549e · outbound

This paper cites A convnet for the 2020s.

Large Language Model Evaluated Stand-alone Attention-Assisted Graph Neural Network with Spatial and Structural Information Interaction for Precise Endoscopic Image Segmentation A convnet for the 2020s

Reference 12

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Observation c61b725c-8317-4f69-b0bb-dbb26159b7dd · outbound

This paper cites Heterogeneous graph attention network.

Large Language Model Evaluated Stand-alone Attention-Assisted Graph Neural Network with Spatial and Structural Information Interaction for Precise Endoscopic Image Segmentation Heterogeneous graph attention network

Reference 14

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Observation 75a15d89-cd97-4bcc-9bab-55187a7221fd · outbound

This paper cites Graph attention networks: a com- prehensive review of methods and applications.

Large Language Model Evaluated Stand-alone Attention-Assisted Graph Neural Network with Spatial and Structural Information Interaction for Precise Endoscopic Image Segmentation Graph attention networks: a com- prehensive review of methods and applications

Reference 16

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Observation ca626f23-3d64-46ec-8e89-c339f90abd02 · outbound

This paper cites A note on two problems in connexion with graphs.

Large Language Model Evaluated Stand-alone Attention-Assisted Graph Neural Network with Spatial and Structural Information Interaction for Precise Endoscopic Image Segmentation A note on two problems in connexion with graphs

Reference 17

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Observation 3a6c046d-d7e6-431e-a5d3-fe50babdbae5 · outbound

This paper cites Attention is all you need.

Large Language Model Evaluated Stand-alone Attention-Assisted Graph Neural Network with Spatial and Structural Information Interaction for Precise Endoscopic Image Segmentation Attention is all you need

Reference 18

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Observation 7317ea16-1fac-4470-8e96-8833fd10b368 · outbound

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Large Language Model Evaluated Stand-alone Attention-Assisted Graph Neural Network with Spatial and Structural Information Interaction for Precise Endoscopic Image Segmentation Kvasir-seg: A segmented polyp dataset

Reference 19

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

Large Language Model Evaluated Stand-alone Attention-Assisted Graph Neural Network with Spatial and Structural Information Interaction for Precise Endoscopic Image Segmentation Wm-dova maps for accurate polyp highlighting in colonoscopy: Validation vs

Reference 20

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Observation fca69ac5-d4bb-4a2e-9a3b-2efddaa488a8 · outbound

This paper cites A benchmark for endoluminal scene segmentation of colonoscopy images.

Large Language Model Evaluated Stand-alone Attention-Assisted Graph Neural Network with Spatial and Structural Information Interaction for Precise Endoscopic Image Segmentation A benchmark for endoluminal scene segmentation of colonoscopy images

Reference 21

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Observation 2a109a69-c8af-4ca0-9f21-8ef3a4d98ac8 · outbound

This paper cites Automated polyp detection in colonoscopy videos using shape and context information.

Large Language Model Evaluated Stand-alone Attention-Assisted Graph Neural Network with Spatial and Structural Information Interaction for Precise Endoscopic Image Segmentation Automated polyp detection in colonoscopy videos using shape and context information

Reference 22

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Observation 5cde632e-5410-4357-8174-94eebadc08e2 · outbound

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

Large Language Model Evaluated Stand-alone Attention-Assisted Graph Neural Network with Spatial and Structural Information Interaction for Precise Endoscopic Image Segmentation U-net: Convolutional networks for biomedical image segmentation

Reference 23

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Observation 20f17e2d-5e5f-4d0d-804d-e9751a7bbbf1 · outbound

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

Large Language Model Evaluated Stand-alone Attention-Assisted Graph Neural Network with Spatial and Structural Information Interaction for Precise Endoscopic Image Segmentation Unet++: A nested u-net architecture for medical image segmen- tation

Reference 24

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Observation 88dbdf0f-c9f0-4ae3-b121-1a31ebf0498a · outbound

This paper cites Dcr-net: Dilated convolutional residual network for fashion image retrieval.

Large Language Model Evaluated Stand-alone Attention-Assisted Graph Neural Network with Spatial and Structural Information Interaction for Precise Endoscopic Image Segmentation Dcr-net: Dilated convolutional residual network for fashion image retrieval

Reference 25

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Observation f2aaecd1-a934-4235-90f1-07bfa8d2490b · outbound

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

Large Language Model Evaluated Stand-alone Attention-Assisted Graph Neural Network with Spatial and Structural Information Interaction for Precise Endoscopic Image Segmentation U-kan makes strong backbone for medical im- age segmentation and generation

Reference 26

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Observation 2eaaaf5c-de11-4b81-bc00-6615a72aeb40 · outbound

This paper cites Structure-measure: A new way to eval- uate foreground maps.

Large Language Model Evaluated Stand-alone Attention-Assisted Graph Neural Network with Spatial and Structural Information Interaction for Precise Endoscopic Image Segmentation Structure-measure: A new way to eval- uate foreground maps

Reference 27

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Observation 1eec1605-ddb9-4d29-abf6-1cf8de39d72f · outbound

This paper cites Individual comparisons by ranking methods.

Large Language Model Evaluated Stand-alone Attention-Assisted Graph Neural Network with Spatial and Structural Information Interaction for Precise Endoscopic Image Segmentation Individual comparisons by ranking methods

Reference 28

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Reference 29

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Observation 683e817c-c180-452f-adf1-916b9d178031 · outbound

This paper cites Llm-seg: Bridging image segmentation and large language model reasoning.

Large Language Model Evaluated Stand-alone Attention-Assisted Graph Neural Network with Spatial and Structural Information Interaction for Precise Endoscopic Image Segmentation Llm-seg: Bridging image segmentation and large language model reasoning

Reference 30

Resolution
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Reference 31

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Reference 32

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Reference 33

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Observation 754d04c2-0764-4802-85a7-048f6cb8c8d0 · outbound

This paper cites Diffusion models: A comprehen- sive survey of methods and applications.

Large Language Model Evaluated Stand-alone Attention-Assisted Graph Neural Network with Spatial and Structural Information Interaction for Precise Endoscopic Image Segmentation Diffusion models: A comprehen- sive survey of methods and applications

Reference 34

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Pith citing papers

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