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Source: paper_references, paper_reference_links, observed 2026-08-05T22:26:53.242434Z
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 17 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.
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Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
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Source: cited_works
Reference resolution
34 of 34 outbound references displayed
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- verified fuzzy26
- unresolved7
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External citation measurements
No source-named external measurement is stored.
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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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
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
- Resolution
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Source-reported events for the cited work
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Observation 6a822af6-bad7-4554-9de6-5bdd22707980 · outbound
This paper cites Polyp-PVT: Polyp Segmentation with Pyramid Vision Transformers.
Large Language Model Evaluated Stand-alone Attention-Assisted Graph Neural Network with Spatial and Structural Information Interaction for Precise Endoscopic Image Segmentation Polyp-PVT: Polyp Segmentation with Pyramid Vision Transformers
Reference 3
- Resolution
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Source-reported events for the cited work
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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
- Resolution
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Source-reported events for the cited work
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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
- Resolution
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Source-reported events for the cited work
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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
- Resolution
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Source-reported events for the cited work
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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
- Resolution
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Source-reported events for the cited work
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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
- Resolution
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Source-reported events for the cited work
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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
- Resolution
- verified fuzzy
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Source-reported events for the cited work
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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
- Resolution
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Source-reported events for the cited work
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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
- Resolution
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Source-reported events for the cited work
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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
- Resolution
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Source-reported events for the cited work
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Observation b52a9df9-e579-4632-b32e-719af7e1caba · outbound
This paper cites Graph Attention Networks.
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
Reference 13
- Resolution
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Source-reported events for the cited work
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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
- Resolution
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Source-reported events for the cited work
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Observation 6ec70476-2e33-4f79-975a-527f0ccfe9a1 · outbound
This paper cites SPAGAN: Shortest Path 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 SPAGAN: Shortest Path Graph Attention Network
Reference 15
- Resolution
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Source-reported events for the cited work
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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
- Resolution
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Source-reported events for the cited work
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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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Source-reported events for the cited work
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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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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 7317ea16-1fac-4470-8e96-8833fd10b368 · outbound
This paper cites Kvasir-seg: A segmented polyp dataset.
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
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation e01217e1-fc53-40cf-a9bf-48e2935697ab · outbound
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
- Resolution
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Source-reported events for the cited work
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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
- Resolution
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Source-reported events for the cited work
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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
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
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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Source-reported events for the cited work
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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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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
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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Source-reported events for the cited work
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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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Source-reported events for the cited work
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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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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
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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Source-reported events for the cited work
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Observation 53c69dd0-5a1b-4817-b0cd-4dd27368b0f4 · outbound
This paper cites Training-Free Semantic Segmentation via LLM-Supervision.
Large Language Model Evaluated Stand-alone Attention-Assisted Graph Neural Network with Spatial and Structural Information Interaction for Precise Endoscopic Image Segmentation Training-Free Semantic Segmentation via LLM-Supervision
Reference 29
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Source-reported events for the cited work
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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
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation b59ff3b7-b109-43b2-a619-846cb26a42b5 · outbound
This paper cites Pre-Trained LLM is a Semantic-Aware and Generalizable Segmentation Booster.
Large Language Model Evaluated Stand-alone Attention-Assisted Graph Neural Network with Spatial and Structural Information Interaction for Precise Endoscopic Image Segmentation Pre-Trained LLM is a Semantic-Aware and Generalizable Segmentation Booster
Reference 31
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Source-reported events for the cited work
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Observation 57d951b4-0b73-4cb6-a617-f17a92f177f8 · outbound
This paper cites Mamba: Linear-Time Sequence Modeling with Selective State Spaces.
Large Language Model Evaluated Stand-alone Attention-Assisted Graph Neural Network with Spatial and Structural Information Interaction for Precise Endoscopic Image Segmentation Mamba: Linear-Time Sequence Modeling with Selective State Spaces
Reference 32
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 961d5e51-33b4-427d-bce4-be72f1563a6b · outbound
This paper cites KAN: Kolmogorov-Arnold Networks.
Large Language Model Evaluated Stand-alone Attention-Assisted Graph Neural Network with Spatial and Structural Information Interaction for Precise Endoscopic Image Segmentation KAN: Kolmogorov-Arnold Networks
Reference 33
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
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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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Pith citing papers
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