Paper Citation Record · LEDGER

Federated Foundation Model for GI Endoscopy Images

As of 20 August 2026, this Paper Citation Record lists 42 of 42 outbound references and 2 inbound Pith citation observations for arXiv:2505.24108.

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

pith.paper-citation-record.v1
2505.24108 v2

Coverage vector

measured 42 of 42 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T12:39:28.209586Z

measured 44 of 44 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-07-13T09:18:06.363249Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-10T22:15:51.436340Z

Reference resolution

42 of 42 outbound references displayed

verified exact4
verified fuzzy18
unresolved18
parse uncertain0
malformed identifier2
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 58346e5a-4648-4762-8cee-d2c45272d41c · outbound

This paper cites Gastrovision: A multi-class endoscopy image dataset for computer aided gastrointestinal disease detection,.

Federated Foundation Model for GI Endoscopy Images Gastrovision: A multi-class endoscopy image dataset for computer aided gastrointestinal disease detection,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:39:34.323029Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation a75084aa-58d8-4bc5-81fd-55a73550b613 · outbound

This paper cites Artificial intelligence in gastrointestinal endoscopy,.

Federated Foundation Model for GI Endoscopy Images Artificial intelligence in gastrointestinal endoscopy,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:39:34.019902Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 82f88c5a-1f66-4f10-a96e-826492e10a99 · outbound

This paper cites Effect of a deep learning–based automatic upper gi endoscopic reporting system: a randomized crossover study (with video),.

Federated Foundation Model for GI Endoscopy Images Effect of a deep learning–based automatic upper gi endoscopic reporting system: a randomized crossover study (with video),

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:39:33.756307Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 86acaf3a-ac02-4a1f-bcc9-09674cdee294 · outbound

This paper cites Deep convolutional neural networks for computer-aided detection: Cnn architectures, dataset characteristics and transfer learning,.

Federated Foundation Model for GI Endoscopy Images Deep convolutional neural networks for computer-aided detection: Cnn architectures, dataset characteristics and transfer learning,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:39:33.530830Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 779c6cb7-a8a7-4e85-a955-aab5592199ef · outbound

This paper cites Deep residual learning for image recognition,.

Federated Foundation Model for GI Endoscopy Images Deep residual learning for image recognition,

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-07T12:39:17.203350Z

Source-reported events for the cited work

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Observation d96a370c-7b91-4bb6-983d-0253c4f93619 · outbound

This paper cites An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale.

Federated Foundation Model for GI Endoscopy Images An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-07T12:39:17.347640Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a30bb2e3-c47a-4ced-be23-fa851eaf4ba5 · outbound

This paper cites Automated polyp detection in colon capsule endoscopy,.

Federated Foundation Model for GI Endoscopy Images Automated polyp detection in colon capsule endoscopy,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:39:33.311016Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation c88d7587-59c3-44b7-83d2-48e492059a84 · outbound

This paper cites Deep learning for detection and segmentation of artefact and disease instances in gastrointestinal endoscopy,.

Federated Foundation Model for GI Endoscopy Images Deep learning for detection and segmentation of artefact and disease instances in gastrointestinal endoscopy,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:39:33.008941Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 92c77a42-6e64-4ad6-bb66-484c003495d9 · outbound

This paper cites Novel deep learning–based computer-aided diag- nosis system for predicting inflammatory activity in ulcerative colitis,.

Federated Foundation Model for GI Endoscopy Images Novel deep learning–based computer-aided diag- nosis system for predicting inflammatory activity in ulcerative colitis,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:39:32.703802Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 0f49bd03-0666-485c-9fbb-2fbab732ef90 · outbound

This paper cites Foundation model for endoscopy video analysis via large-scale self-supervised pre-train,.

Federated Foundation Model for GI Endoscopy Images Foundation model for endoscopy video analysis via large-scale self-supervised pre-train,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:39:32.377101Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 4fbe0921-c97b-45fe-a7bf-1e1d7a6a0470 · outbound

This paper cites A foundation model for generalizable disease detection from retinal images,.

Federated Foundation Model for GI Endoscopy Images A foundation model for generalizable disease detection from retinal images,

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-07T12:39:17.943515Z

Source-reported events for the cited work

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Observation b59ee7a2-7462-4010-93c7-3afa67a12d3b · outbound

This paper cites Masked au- toencoders are scalable vision learners,.

Federated Foundation Model for GI Endoscopy Images Masked au- toencoders are scalable vision learners,

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-07T12:39:18.147222Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5bfe7e36-8cc7-4f8d-8676-06c91e51b37f · outbound

This paper cites A simple framework for contrastive learning of visual representations,.

Federated Foundation Model for GI Endoscopy Images A simple framework for contrastive learning of visual representations,

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-07T12:39:18.239391Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bc3537ff-231d-4a81-a69e-0ecc55a5e28a · outbound

This paper cites Foundation models defining a new era in vision: a survey and outlook,.

Federated Foundation Model for GI Endoscopy Images Foundation models defining a new era in vision: a survey and outlook,

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-07T12:39:18.363541Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b41be0a3-b5c6-4865-bbcc-f58553cedc59 · outbound

This paper cites Federated learning and differential privacy for medical image analysis,.

Federated Foundation Model for GI Endoscopy Images Federated learning and differential privacy for medical image analysis,

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-07T12:39:18.502212Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 46ca078a-d1b9-4c41-9819-4f855531a74a · outbound

This paper cites Communication-efficient learning of deep networks from decentralized data,.

Federated Foundation Model for GI Endoscopy Images Communication-efficient learning of deep networks from decentralized data,

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-07T12:39:18.632131Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 40ec1393-d139-40ba-8730-3b5f6dca4181 · outbound

This paper cites Multimodal Federated Learning in Healthcare: a Review.

Federated Foundation Model for GI Endoscopy Images Multimodal Federated Learning in Healthcare: a Review

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-07T12:39:18.745205Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 63cbffad-3753-44ad-8ace-81de8c50c918 · outbound

This paper cites Deep learning-based prediction model for diagnosing gastrointestinal diseases using endoscopy images,.

Federated Foundation Model for GI Endoscopy Images Deep learning-based prediction model for diagnosing gastrointestinal diseases using endoscopy images,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:39:32.026892Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 674ae909-3e00-4ae2-a5c3-0d7f5cac0a1a · outbound

This paper cites Development of a real-time endoscopic image diagnosis support system using deep learning technology in colonoscopy,.

Federated Foundation Model for GI Endoscopy Images Development of a real-time endoscopic image diagnosis support system using deep learning technology in colonoscopy,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:39:31.868191Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation da0ede78-6ea2-4bc4-a0f1-4a1ccc382584 · outbound

This paper cites Attention enabled multiresunet for bio-medical image segmentation,.

Federated Foundation Model for GI Endoscopy Images Attention enabled multiresunet for bio-medical image segmentation,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:39:31.692226Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 0fb9aec7-d425-44fb-a214-d14328388333 · outbound

This paper cites Deep-learning system detects neoplasia in patients with barrett’s esophagus with higher accuracy than endoscopists in a multistep training and validation study with benchmarking,.

Federated Foundation Model for GI Endoscopy Images Deep-learning system detects neoplasia in patients with barrett’s esophagus with higher accuracy than endoscopists in a multistep training and validation study with benchmarking,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:39:31.420395Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 20f2fd2c-844d-406d-aa90-ace37dec9b43 · outbound

This paper cites Foundation models in gastrointestinal endoscopic ai: Impact of architecture, pre-training approach and data efficiency,.

Federated Foundation Model for GI Endoscopy Images Foundation models in gastrointestinal endoscopic ai: Impact of architecture, pre-training approach and data efficiency,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:39:31.166195Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 287f2ad6-07cc-4a06-844c-f201714ca65e · outbound

This paper cites EndoDINO: A Foundation Model for GI Endoscopy.

Federated Foundation Model for GI Endoscopy Images EndoDINO: A Foundation Model for GI Endoscopy

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-07T12:39:25.376856Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 74980275-fece-4d2d-9e8b-1005b6c141f7 · outbound

This paper cites Endovit: pretraining vision transformers on a large collection of endoscopic images,.

Federated Foundation Model for GI Endoscopy Images Endovit: pretraining vision transformers on a large collection of endoscopic images,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:39:30.940961Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation aa6baa29-6ec2-43ae-b52e-d026f6147520 · outbound

This paper cites Divergence-aware Federated Self-Supervised Learning.

Federated Foundation Model for GI Endoscopy Images Divergence-aware Federated Self-Supervised Learning

Reference 25

Resolution: verified exact; local_arxiv, observed 2026-08-07T12:39:29.187254Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation c1f690c9-ae7d-41df-a1ce-4e55538adaff · outbound

This paper cites Federated Self-supervised Learning for Heterogeneous Clients.

Federated Foundation Model for GI Endoscopy Images Federated Self-supervised Learning for Heterogeneous Clients

Reference 26

Resolution: verified exact; local_arxiv, observed 2026-08-07T12:39:29.020179Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 076530d7-7632-445f-9925-975db9dba604 · outbound

This paper cites Label-efficient self-supervised federated learning for tackling data heterogeneity in medical imaging,.

Federated Foundation Model for GI Endoscopy Images Label-efficient self-supervised federated learning for tackling data heterogeneity in medical imaging,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:39:30.767839Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 0b38ac50-ee33-4587-99a9-0e327361834b · outbound

This paper cites Fedfms: Exploring federated foundation models for medical image segmentation,.

Federated Foundation Model for GI Endoscopy Images Fedfms: Exploring federated foundation models for medical image segmentation,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:39:30.626689Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation a00fcda0-9d75-42d7-ae86-399ebb262773 · outbound

This paper cites Federated Learning for Medical Image Classification: A Comprehensive Benchmark.

Federated Foundation Model for GI Endoscopy Images Federated Learning for Medical Image Classification: A Comprehensive Benchmark

Reference 29

Resolution: verified exact; local_arxiv, observed 2026-08-07T12:39:28.792631Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation c2af2a53-7d0d-4a7b-b979-dc3a98dd3a38 · outbound

This paper cites Federated endovit: Pretraining vision transformers via federated learning on endoscopic image collec- tions,.

Federated Foundation Model for GI Endoscopy Images Federated endovit: Pretraining vision transformers via federated learning on endoscopic image collec- tions,

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-07T12:39:26.642517Z

Source-reported events for the cited work

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Observation 4400b53b-3d6f-4f8a-b1b0-b35ed4165cdb · outbound

This paper cites Measuring the Effects of Non-Identical Data Distribution for Federated Visual Classification.

Federated Foundation Model for GI Endoscopy Images Measuring the Effects of Non-Identical Data Distribution for Federated Visual Classification

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-07T12:39:26.766818Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation eefa9249-54d1-47ac-801a-6ebd9b8e4abd · outbound

This paper cites Adaptive Federated Optimization.

Federated Foundation Model for GI Endoscopy Images Adaptive Federated Optimization

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-07T12:39:26.857965Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6fc824ff-29e3-498b-8347-0e3ee945d15d · outbound

This paper cites Exploring plain vision transformer backbones for object detection,.

Federated Foundation Model for GI Endoscopy Images Exploring plain vision transformer backbones for object detection,

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-07T12:39:27.024132Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c4e46a35-1012-477a-9f9e-a6d0f1e23ebe · outbound

This paper cites Mask r-cnn,.

Federated Foundation Model for GI Endoscopy Images Mask r-cnn,

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-07T12:39:27.181741Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fb26f3bb-7dfa-4ae1-9b32-4b80b07e7e98 · outbound

This paper cites Hyperkvasir, a comprehensive multi-class image and video dataset for gastrointestinal endoscopy,.

Federated Foundation Model for GI Endoscopy Images Hyperkvasir, a comprehensive multi-class image and video dataset for gastrointestinal endoscopy,

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:39:30.415977Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 49960bff-ca32-4d9d-976a-d9ddb3c2bfe4 · outbound

This paper cites Kvasir-capsule, a video capsule endoscopy dataset,.

Federated Foundation Model for GI Endoscopy Images Kvasir-capsule, a video capsule endoscopy dataset,

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:39:30.232837Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 9cfdb997-893d-4cec-a984-d608be6dd6dd · outbound

This paper cites Endoscopy disease detection and segmentation (edd2020),.

Federated Foundation Model for GI Endoscopy Images Endoscopy disease detection and segmentation (edd2020),

Reference 37

Resolution: verified exact; doi, observed 2026-08-07T12:39:28.435663Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 1ef8b089-5f6c-4c6b-834a-ca90fbf6cc12 · outbound

This paper cites BOLD VALUES INDICATE THE HIGHEST VALUES FOR EACH METRIC , AND UNDERLINED VALUES REPRESENT THE SECOND -HIGHEST VALUES.

Federated Foundation Model for GI Endoscopy Images BOLD VALUES INDICATE THE HIGHEST VALUES FOR EACH METRIC , AND UNDERLINED VALUES REPRESENT THE SECOND -HIGHEST VALUES

Reference 38

Resolution: malformed identifier; raw_fallback, observed 2026-08-07T12:39:30.108182Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation bdccb556-f0b9-45b9-804d-a7815be34ac0 · outbound

This paper cites BOLD VALUES INDICATE THE HIGHEST VALUES FOR EACH METRIC , AND UNDERLINED VALUES REPRESENT THE SECOND -HIGHEST VALUES.

Federated Foundation Model for GI Endoscopy Images BOLD VALUES INDICATE THE HIGHEST VALUES FOR EACH METRIC , AND UNDERLINED VALUES REPRESENT THE SECOND -HIGHEST VALUES

Reference 39

Resolution: malformed identifier; raw_fallback, observed 2026-08-07T12:39:29.885067Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 4e601722-59ed-461e-adc5-f4617b697f50 · outbound

This paper cites an unresolved cited work.

Federated Foundation Model for GI Endoscopy Images Unresolved cited work

Reference 40

Resolution: unresolved; raw_fallback, observed 2026-08-07T12:39:29.654246Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation b8e6a714-ce60-4b92-9f4c-6ab29ecc0fb8 · outbound

This paper cites an unresolved cited work.

Federated Foundation Model for GI Endoscopy Images Unresolved cited work

Reference 41

Resolution: unresolved; raw_fallback, observed 2026-08-07T12:39:29.507911Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation bcf85b6f-3c17-463a-9fd2-8c571e511ac1 · outbound

This paper cites an unresolved cited work.

Federated Foundation Model for GI Endoscopy Images Unresolved cited work

Reference 42

Resolution: unresolved; raw_fallback, observed 2026-08-07T12:39:29.368936Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Pith citing papers

Observation 5eeb0765-236e-4742-9ffb-29a78e935b13 · inbound

Leaderless Collective Motion in Affine Formation Control over the Complex Plane cites this paper.

Leaderless Collective Motion in Affine Formation Control over the Complex Plane Federated Foundation Model for GI Endoscopy Images

Reference 23

Resolution: unresolved; no resolver link, observed 2026-07-13T09:18:06.363249Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5f6de4c4-3906-4833-a32f-742187e9df70 · inbound

Analogical Reasoning as a Doctor: A Foundation Model for Gastrointestinal Endoscopy Diagnosis cites this paper.

Analogical Reasoning as a Doctor: A Foundation Model for Gastrointestinal Endoscopy Diagnosis Federated Foundation Model for GI Endoscopy Images

Reference 23

Resolution: verified exact; arxiv_id, observed 2026-05-10T22:15:51.439532Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.