Typed states for the displayed outbound observations.
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 8 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
- verified exact1
- 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 2026-08-07T06:34:17.273281+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
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
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
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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
Unavailable: canonical work link unavailable.
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
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
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
- verified fuzzy
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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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- verified fuzzy
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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
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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
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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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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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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 2026-08-07T06:34:17.273281+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
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
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
- Resolution
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Source-reported events for the cited work
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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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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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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 2026-08-07T06:34:17.273281+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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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
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
- Resolution
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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
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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
Unavailable: canonical work link unavailable.
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
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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
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Pith citing papers
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