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Paper Citation Record · LEDGER

Subspecialty-Specific Foundation Model for Intelligent Gastrointestinal Pathology

As of 9 August 2026, this Paper Citation Record lists 52 of 52 outbound references and 1 inbound Pith citation observation for arXiv:2505.21928.

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

pith.paper-citation-record.v1
2505.21928 v2

Coverage vector

measured 52 of 52 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T13:26:39.674919Z

measured 53 of 53 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-12T00:58:28.390860Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-12T08:36:24.490729Z

Reference resolution

52 of 52 outbound references displayed

  • verified exact1
  • verified fuzzy37
  • unresolved14
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation a8481021-ce1c-4237-a647-205dfe660553 · outbound

This paper cites Global burden of five major types of gastrointestinalcancer[J].PrzGastroenterol.2024;19(3):236–254.

Subspecialty-Specific Foundation Model for Intelligent Gastrointestinal Pathology Global burden of five major types of gastrointestinalcancer[J].PrzGastroenterol.2024;19(3):236–254

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:26:47.428588Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T13:26:34.867834Z digest=sha256:59599c3ee3fd4a3f98f7f9b7fcf6e0cec0ce27fc48074b84ff4428737b21521c

Observation 40921485-5b94-429c-918f-83a3e043fbd8 · outbound

This paper cites Concomitant radiosurgical and targeted oncological treatment improves the outcome of patients with brain metastases from gastrointestinalcancer.RadiatOncol.2023Dec9;18(1):197.

Subspecialty-Specific Foundation Model for Intelligent Gastrointestinal Pathology Concomitant radiosurgical and targeted oncological treatment improves the outcome of patients with brain metastases from gastrointestinalcancer.RadiatOncol.2023Dec9;18(1):197

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:26:47.310031Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T13:26:35.048999Z digest=sha256:f7e83744900b467dce5e71e6cec1e96ca02d73fce485061b76e4e9c8370c2dec

Observation ad047c47-0c70-43c0-bb10-6bfd72a39488 · outbound

This paper cites Multiscale pretraining enables robust representation.

Subspecialty-Specific Foundation Model for Intelligent Gastrointestinal Pathology Multiscale pretraining enables robust representation

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:26:48.260517Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T13:26:34.174551Z digest=sha256:d6a02cb28f22acd07e40e2dddece14200829bfc7fa95ad9c9ff68e16ad6f490c

Observation ffde322a-c4e3-4741-a5a3-3ef90da7819e · outbound

This paper cites an unresolved cited work.

Subspecialty-Specific Foundation Model for Intelligent Gastrointestinal Pathology Unresolved cited work

Reference 4

Resolution
unresolved
raw_fallback, observed 2026-08-07T13:26:48.035757Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T13:26:34.322456Z digest=sha256:94a2b9ffeb0a9c758bfb81944641075d2e81ef17187461539a78a985c316e781

Observation 9197a4bb-3981-49b6-86b8-cf7db312399d · outbound

This paper cites an unresolved cited work.

Subspecialty-Specific Foundation Model for Intelligent Gastrointestinal Pathology Unresolved cited work

Reference 5

Resolution
unresolved
raw_fallback, observed 2026-08-07T13:26:47.791320Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T13:26:34.496558Z digest=sha256:82bdb588ad5c47a1fb5803e3e646835fe4ffae681e7af2125e449354a28b7a21

Observation 71d12b1b-5e7f-427a-8fab-af13e501a3d9 · outbound

This paper cites In few-shot learning, the choice of 'way' has a significant impact on task difficulty and model performance.

Subspecialty-Specific Foundation Model for Intelligent Gastrointestinal Pathology In few-shot learning, the choice of 'way' has a significant impact on task difficulty and model performance

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:26:47.643903Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T13:26:34.631606Z digest=sha256:77363fe39f5c911c85664fac8d131a697085b89529098f3d670be785df212617

Observation 4919a661-591b-408a-a6a2-489b39df557b · outbound

This paper cites The ProtoNet first convert all training images into embedding vectors, then performs mean-poolingonembeddingsofthesamecategorytoobtainprototyperepresentations.

Subspecialty-Specific Foundation Model for Intelligent Gastrointestinal Pathology The ProtoNet first convert all training images into embedding vectors, then performs mean-poolingonembeddingsofthesamecategorytoobtainprototyperepresentations

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:26:47.551550Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T13:26:34.752346Z digest=sha256:617dc628f66ea69fc4c8d8fb629dc8c615491f0e56a87f18b1a6596c96463b34

Observation 8f3f488a-5721-47f4-8702-6325afe6a860 · outbound

This paper cites Global Cancer Observatory: Cancer Today (Version1.0).InternationalAgencyforResearchonCancer; 2024.AccessedFebruary 1,2024.

Subspecialty-Specific Foundation Model for Intelligent Gastrointestinal Pathology Global Cancer Observatory: Cancer Today (Version1.0).InternationalAgencyforResearchonCancer; 2024.AccessedFebruary 1,2024

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:26:47.186735Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T13:26:35.192204Z digest=sha256:860c636b078f64bad659af816351b87c59f1c04fc41e5f7008e3af133f89d303

Observation 7529510b-f870-4f25-86cd-a30e6f1703be · outbound

This paper cites Practical Considerations in Diagnosing and Managing Early-OnsetGICancers[J].JClinOncol.2022Aug20;40(24):2662–2680.

Subspecialty-Specific Foundation Model for Intelligent Gastrointestinal Pathology Practical Considerations in Diagnosing and Managing Early-OnsetGICancers[J].JClinOncol.2022Aug20;40(24):2662–2680

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:26:47.066097Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T13:26:35.318346Z digest=sha256:2493978b1ea5a02df79859221b07096727531dcbb7cfe8411655b35ef2c6366f

Observation b199a8b8-c859-4f0f-8b5f-30951b5927be · outbound

This paper cites Diagnosis to dissection: AI's role in earlydetection andsurgical intervention for gastric cancer[J].JRobot Surg.

Subspecialty-Specific Foundation Model for Intelligent Gastrointestinal Pathology Diagnosis to dissection: AI's role in earlydetection andsurgical intervention for gastric cancer[J].JRobot Surg

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:26:46.897213Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T13:26:35.437101Z digest=sha256:fce0c626ae81257daf0ad835bc6b913a945b64b1fb1d54ebcd89878fe0babcbd

Observation 118c0fdc-cae2-405b-b14d-1fab4c5e0b72 · outbound

This paper cites an unresolved cited work.

Subspecialty-Specific Foundation Model for Intelligent Gastrointestinal Pathology Unresolved cited work

Reference 11

Resolution
unresolved
raw_fallback, observed 2026-08-07T13:26:46.701233Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T13:26:35.541601Z digest=sha256:9cebeb4dfdf3c1ffac7de86b963677e91d66442705a3e8741f6a5c09b72266e4

Observation 6d604134-808b-417e-b6a5-67ab27e1a574 · outbound

This paper cites an unresolved cited work.

Subspecialty-Specific Foundation Model for Intelligent Gastrointestinal Pathology Unresolved cited work

Reference 12

Resolution
unresolved
raw_fallback, observed 2026-08-07T13:26:46.550495Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T13:26:35.635274Z digest=sha256:4a561e5b9ad1c44ec48ecb6e0d79fb735c5da17abace2d9360231986f2d770d2

Observation 70e1bae6-4911-4963-9e95-0f937a5a4afb · outbound

This paper cites Opening the doors of precision medicine: novel tools to assess intestinal barrier in inflammatory bowel disease and colitis-associatedneoplasia[J].Gut,2024,73(10):1749–1762.

Subspecialty-Specific Foundation Model for Intelligent Gastrointestinal Pathology Opening the doors of precision medicine: novel tools to assess intestinal barrier in inflammatory bowel disease and colitis-associatedneoplasia[J].Gut,2024,73(10):1749–1762

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:26:46.405088Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T13:26:35.716574Z digest=sha256:c898446fa740d593150f445a35523e256d924fd914c95bf2c6d2446d361d0048

Observation 8b900e5f-66cd-48a8-8231-cf1a8c815ce7 · outbound

This paper cites Artificial intelligence in digital pathology: a systematic review and meta-analysis of diagnostic test accuracy[J].

Subspecialty-Specific Foundation Model for Intelligent Gastrointestinal Pathology Artificial intelligence in digital pathology: a systematic review and meta-analysis of diagnostic test accuracy[J]

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:26:46.190382Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T13:26:35.824370Z digest=sha256:f2da62cdc89173af19c5f1c97536d964df9a6f091adcbc47fd0b0fb7b12042f1

Observation 329815be-f5bc-4b06-8be1-b25d7e3b4334 · outbound

This paper cites Sequential injection-electrocoagulation vs.

Subspecialty-Specific Foundation Model for Intelligent Gastrointestinal Pathology Sequential injection-electrocoagulation vs

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:26:46.015546Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T13:26:35.947667Z digest=sha256:c28fad7e614916707536d46f5fb6cdb372bd32dfce9d6eda73425bb2a599d050

Observation c8473f24-2c8a-4276-9539-a622e1456931 · outbound

This paper cites Updated evaluation of endoscopic submucosal dissection versus surgery for early gastric cancer: A systematic review and meta-analysis[J].InternationalJournalofSurgery,2020,73:28–41.

Subspecialty-Specific Foundation Model for Intelligent Gastrointestinal Pathology Updated evaluation of endoscopic submucosal dissection versus surgery for early gastric cancer: A systematic review and meta-analysis[J].InternationalJournalofSurgery,2020,73:28–41

Reference 16

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:26:45.833130Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T13:26:36.043938Z digest=sha256:f50ebc098ea2183623cf153c8ddb6d5ea5f1b39b898e7e989ffd9e810fa4b5ac

Observation a62d9d95-f597-4d33-90ff-d7683acd7373 · outbound

This paper cites Incidence of metachronous cancer after endoscopic submucosal dissection: a comparison between undifferentiated-type and differentiated-type early gastric cancer[J].

Subspecialty-Specific Foundation Model for Intelligent Gastrointestinal Pathology Incidence of metachronous cancer after endoscopic submucosal dissection: a comparison between undifferentiated-type and differentiated-type early gastric cancer[J]

Reference 17

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:26:45.621320Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T13:26:36.145728Z digest=sha256:c953e0dbcc98b774d59621770558eca2cd0dcc84b0687c95c3ab27c6c77c781f

Observation f8369d11-90eb-4541-ae2e-73c7eae54bee · outbound

This paper cites Endoscopic submucosal dissection forearlygastriccancer:alarge-scalefeasibilitystudy[J].Gut,2009,58(3):331–336.

Subspecialty-Specific Foundation Model for Intelligent Gastrointestinal Pathology Endoscopic submucosal dissection forearlygastriccancer:alarge-scalefeasibilitystudy[J].Gut,2009,58(3):331–336

Reference 18

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:26:45.492653Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T13:26:36.295851Z digest=sha256:8bcf80899c9ffe75d5f7c10fd92cfb76377dac42385f952942981cea73bc3b16

Observation 86ce1583-d49d-494e-bc6f-3edfa21a3a19 · outbound

This paper cites Surgical management of gastric cancer: a review[J].JAMAsurgery,2022,157(5):446–454.

Subspecialty-Specific Foundation Model for Intelligent Gastrointestinal Pathology Surgical management of gastric cancer: a review[J].JAMAsurgery,2022,157(5):446–454

Reference 19

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:26:45.294962Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T13:26:36.407767Z digest=sha256:bb0099fd5ed357a6ee46c88f811a47dd541757ab4095ff04c066397c0959332f

Observation 490fc85a-9c3b-4334-ba1e-d0887259c78a · outbound

This paper cites Focus on gastric cancer[J].

Subspecialty-Specific Foundation Model for Intelligent Gastrointestinal Pathology Focus on gastric cancer[J]

Reference 20

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:26:45.152692Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T13:26:36.487844Z digest=sha256:d743b8591b6c7603a27300d2040d9cad2e27402019cd098a5c69bcbe52339d15

Observation a8fd647d-67ad-40a6-b718-7b2abebc6b79 · outbound

This paper cites Staging and surgical approaches in gastric cancer:Asystematicreview[J].Cancertreatmentreviews,2018,63:104–115.

Subspecialty-Specific Foundation Model for Intelligent Gastrointestinal Pathology Staging and surgical approaches in gastric cancer:Asystematicreview[J].Cancertreatmentreviews,2018,63:104–115

Reference 21

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:26:44.938597Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T13:26:36.570492Z digest=sha256:a219644ffcfe8467d9bb9b888c5919f42a294e1b9e606c15970f4bc2e615b498

Observation 3c9e6930-8d49-4d00-aec6-2eadc3b02ea3 · outbound

This paper cites Gastric cancer treatment: recent progress and future perspectives[J].Journalofhematology&oncology,2023,16(1):57.

Subspecialty-Specific Foundation Model for Intelligent Gastrointestinal Pathology Gastric cancer treatment: recent progress and future perspectives[J].Journalofhematology&oncology,2023,16(1):57

Reference 23

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:26:44.752633Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T13:26:36.667821Z digest=sha256:74f9876ceab865b0bb9e49a956df07b96caca51c76def295e4971d62fccf3f3c

Observation 1241cfde-2760-4b50-8f65-2d8bb53ba13a · outbound

This paper cites Hallmarks of artificial intelligence contributionstoprecisiononcology[J].NatureCancer,2025:1–15.

Subspecialty-Specific Foundation Model for Intelligent Gastrointestinal Pathology Hallmarks of artificial intelligence contributionstoprecisiononcology[J].NatureCancer,2025:1–15

Reference 25

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:26:44.559131Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T13:26:36.757099Z digest=sha256:ca737802b101b856311a4535a113e4d5d1abb2a10609fa2b3c0e62a091975121

Observation 319813e1-4b52-49ff-9bb1-18a576dafcf5 · outbound

This paper cites A comprehensive assessment of artificial intelligence applications for cancer diagnosis[J].Artificial Intelligence Review, 2024, 57(7):179.

Subspecialty-Specific Foundation Model for Intelligent Gastrointestinal Pathology A comprehensive assessment of artificial intelligence applications for cancer diagnosis[J].Artificial Intelligence Review, 2024, 57(7):179

Reference 26

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:26:44.338047Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T13:26:36.835948Z digest=sha256:fb4ebb8fe9fb175ea64347e8f0a004423d8c8e7648d1bc7d92e01d50553ea00e

Observation d435b31d-7bb0-4066-8d90-ee68f20a4128 · outbound

This paper cites A pathologist–AI collaboration framework for enhancing diagnostic accuracies and efficiencies[J].

Subspecialty-Specific Foundation Model for Intelligent Gastrointestinal Pathology A pathologist–AI collaboration framework for enhancing diagnostic accuracies and efficiencies[J]

Reference 27

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:26:44.120028Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T13:26:36.939619Z digest=sha256:20bab45ee28abf19497cc9501577b48a3c8e7d7a9fffc736e8a1c5c1fb9a35ff

Observation 134fed3e-ea2d-4d21-9db8-3c4b6ac83a50 · outbound

This paper cites AI in digital pathology: automated histopathological analysis for cancergradingandprognosticoutcomeprediction[J].IntJComputApplTechnolRes, 2022,11(11):400–12.

Subspecialty-Specific Foundation Model for Intelligent Gastrointestinal Pathology AI in digital pathology: automated histopathological analysis for cancergradingandprognosticoutcomeprediction[J].IntJComputApplTechnolRes, 2022,11(11):400–12

Reference 28

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:26:43.913986Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T13:26:37.036848Z digest=sha256:124c267607754da6019684dc28305268da02bb71af421bedd8d84422eea65fef

Observation 67542027-66b7-4489-9d77-3e439411bb84 · outbound

This paper cites an unresolved cited work.

Subspecialty-Specific Foundation Model for Intelligent Gastrointestinal Pathology Unresolved cited work

Reference 30

Resolution
unresolved
raw_fallback, observed 2026-08-07T13:26:43.664003Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T13:26:37.088712Z digest=sha256:45b15e525676f086fdb71bf1d3eab58ba38410d9b9fda5696a710c4cab862407

Observation cff89dcf-51e8-4d57-ad1e-d1a26f2f1648 · outbound

This paper cites Foundation Models Defining a New Era in Vision:ASurveyandOutlook[J].IEEETransactionsonPatternAnalysisandMachine Intelligence,2025.

Subspecialty-Specific Foundation Model for Intelligent Gastrointestinal Pathology Foundation Models Defining a New Era in Vision:ASurveyandOutlook[J].IEEETransactionsonPatternAnalysisandMachine Intelligence,2025

Reference 31

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:26:43.448157Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T13:26:37.149812Z digest=sha256:2df22fa2cea70ff45abafa7dd6669fc7a504f2973c1339ff0b78511ec7e2a2b4

Observation d5527cb2-28d6-43fb-ae77-6e795b4f0023 · outbound

This paper cites An empirical study of training self-supervised vision transformers.In:ProceedingsIEEE/CVFIntConfComputVis.2021:9640–9649.

Subspecialty-Specific Foundation Model for Intelligent Gastrointestinal Pathology An empirical study of training self-supervised vision transformers.In:ProceedingsIEEE/CVFIntConfComputVis.2021:9640–9649

Reference 32

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:26:43.225545Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T13:26:37.237165Z digest=sha256:2d2a2430a294b6106ac61f5d3d80be7c86073861ec88df260ef3bcb63ccce033

Observation 9a2b8104-a8b1-4a81-be1d-f8800c896e6c · outbound

This paper cites Foundation Model for Predicting Prognosis and Adjuvant Therapy Benefit From Digital Pathology in GI Cancers[J].

Subspecialty-Specific Foundation Model for Intelligent Gastrointestinal Pathology Foundation Model for Predicting Prognosis and Adjuvant Therapy Benefit From Digital Pathology in GI Cancers[J]

Reference 33

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:26:43.019404Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T13:26:37.355283Z digest=sha256:b13562dfe2e6aa06ab5340ffdde798b5c43717e251d555e162d5aa60799e0dfd

Observation e3d58e9c-7cc3-401c-9926-c7412425937e · outbound

This paper cites CellViT++: Energy-Efficient and Adaptive Cell Segmentation and Classification Using Foundation Models.

Subspecialty-Specific Foundation Model for Intelligent Gastrointestinal Pathology CellViT++: Energy-Efficient and Adaptive Cell Segmentation and Classification Using Foundation Models

Reference 34

Resolution
unresolved
no resolver link, observed 2026-08-07T13:26:37.468744Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:26:37.468744Z digest=sha256:e6ae165354981fe834c63a02069f09b2c88ac18f768e3685a13aa659e184a2cd

Observation f4c8b71f-445a-48e3-a488-19016cc7320f · outbound

This paper cites A pathology foundation model for cancer diagnosisandprognosisprediction[J].Nature,2024,634(8035):970–978.

Subspecialty-Specific Foundation Model for Intelligent Gastrointestinal Pathology A pathology foundation model for cancer diagnosisandprognosisprediction[J].Nature,2024,634(8035):970–978

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:26:42.836172Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T13:26:37.531793Z digest=sha256:5963b52560ea20b3422405a0e0f7d20e78d5a044d43cfab5040762b37ae33f5e

Observation 087ec1bd-f9dc-4869-8ebc-ad11aa536c2a · outbound

This paper cites an unresolved cited work.

Subspecialty-Specific Foundation Model for Intelligent Gastrointestinal Pathology Unresolved cited work

Reference 36

Resolution
unresolved
raw_fallback, observed 2026-08-07T13:26:42.648336Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T13:26:37.638337Z digest=sha256:a66f780d627a0c5e1c0f699fbafc982c7e0226cadb9859b0c9adc533e0848212

Observation 6fd2c5d2-5da4-44a1-a45a-1d3caa67392a · outbound

This paper cites A whole-slide foundation model for digital pathologyfromreal-worlddata[J].Nature.2024;630:181–188.

Subspecialty-Specific Foundation Model for Intelligent Gastrointestinal Pathology A whole-slide foundation model for digital pathologyfromreal-worlddata[J].Nature.2024;630:181–188

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:26:42.435531Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T13:26:37.776306Z digest=sha256:3b01e5c5262a5cdda0e30cfbd195d316164c5d04dd48d045bea92297ace21905

Observation 3af57d58-4608-4b23-85e0-34d7e982f58a · outbound

This paper cites Multimodal Whole Slide Foundation Model for Pathology.

Subspecialty-Specific Foundation Model for Intelligent Gastrointestinal Pathology Multimodal Whole Slide Foundation Model for Pathology

Reference 38

Resolution
unresolved
no resolver link, observed 2026-08-07T13:26:37.892246Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:26:37.892246Z digest=sha256:63558142029c854d5e34ac9de8424724a5ef55d0872bcb63bb16dad7f28be074

Observation befef4a4-4882-4f06-904b-eae5cc73e5a7 · outbound

This paper cites MSCL-Net: Unleashing thepower of multi-scale and cross-layer learning in pathology image classification[J].

Subspecialty-Specific Foundation Model for Intelligent Gastrointestinal Pathology MSCL-Net: Unleashing thepower of multi-scale and cross-layer learning in pathology image classification[J]

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:26:42.222226Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T13:26:37.994214Z digest=sha256:0a86565da2bc1e9cb5adf7ed35ea5cd7d4e29d37bad5b122d686dd0f20e4f6c6

Observation 3d944ca4-ecf6-4103-98f1-bdcc97d71689 · outbound

This paper cites Multi-Scale Dynamic Sparse Token Multi-Instance Learning for Pathology Image Classification[J].

Subspecialty-Specific Foundation Model for Intelligent Gastrointestinal Pathology Multi-Scale Dynamic Sparse Token Multi-Instance Learning for Pathology Image Classification[J]

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:26:42.045230Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T13:26:38.098256Z digest=sha256:ab81637b3636b5c4c88c9c5efb8f88da9f786ddfb3d1b773447eecff4ad50f14

Observation eb5e680e-30e6-4bb9-9827-b6be4604062e · outbound

This paper cites Clinically applicable histopathological diagnosis system for gastric cancer detection using deep learning[J].

Subspecialty-Specific Foundation Model for Intelligent Gastrointestinal Pathology Clinically applicable histopathological diagnosis system for gastric cancer detection using deep learning[J]

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:26:41.827941Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T13:26:38.234264Z digest=sha256:8e14bc3276880dafc5fa1dbef18ae4d3a1028be4f2f078b26cdf435596dd87b3

Observation 2f1061d8-e565-4a9c-abb0-aab714037b4f · outbound

This paper cites Reinforcement Learning Finetunes Small Subnetworks in Large Language Models[J].

Subspecialty-Specific Foundation Model for Intelligent Gastrointestinal Pathology Reinforcement Learning Finetunes Small Subnetworks in Large Language Models[J]

Reference 43

Resolution
unresolved
no resolver link, observed 2026-08-07T13:26:38.363753Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:26:38.363753Z digest=sha256:c4042d4dbff7b1e6bd21e5b990f7df2bc666a81c8ecdc910e242ef154043c3b6

Observation 334ed5dd-db09-433e-9b6c-cd103daf7ca4 · outbound

This paper cites EMORL: Ensemble Multi-Objective Reinforcement Learning for Efficient and Flexible LLM Fine-Tuning.

Subspecialty-Specific Foundation Model for Intelligent Gastrointestinal Pathology EMORL: Ensemble Multi-Objective Reinforcement Learning for Efficient and Flexible LLM Fine-Tuning

Reference 44

Resolution
unresolved
no resolver link, observed 2026-08-07T13:26:38.470669Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:26:38.470669Z digest=sha256:e63e715717442f3806c9d99ba6163aee6d376dabdd499c8581fd8250b9826572

Observation 9d6a6de4-fa73-4ec8-b2ce-6a4df7c5f4fc · outbound

This paper cites Transfer learning with adaptive fine-tuning[J].

Subspecialty-Specific Foundation Model for Intelligent Gastrointestinal Pathology Transfer learning with adaptive fine-tuning[J]

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:26:41.645338Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T13:26:38.575803Z digest=sha256:13a4bbe874a5a837e374b3476320b5678d0c71ec079542b9557417c61c44419e

Observation 7d37e720-9627-43f2-97c7-23141b14b406 · outbound

This paper cites DINOv2: Learning Robust Visual Features without Supervision.

Subspecialty-Specific Foundation Model for Intelligent Gastrointestinal Pathology DINOv2: Learning Robust Visual Features without Supervision

Reference 46

Resolution
unresolved
no resolver link, observed 2026-08-07T13:26:38.709616Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:26:38.709616Z digest=sha256:e55d0aa7d3e7f49ee5e8fdf5fc69adda8495218afdcfa924faad15441ab406a7

Observation 9145db3f-c59c-4271-9204-fb5d20f8a7bb · outbound

This paper cites Attention-based deep multiple instance learning[C]//Internationalconferenceonmachinelearning.PMLR,2018:2127–2136.

Subspecialty-Specific Foundation Model for Intelligent Gastrointestinal Pathology Attention-based deep multiple instance learning[C]//Internationalconferenceonmachinelearning.PMLR,2018:2127–2136

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:26:41.457001Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T13:26:38.779858Z digest=sha256:0d641b8a58ae0ec004db7f2a3158fb8065a9f8434a3591114d2cd20665b010eb

Observation ce791e27-67ca-4a00-bb47-f1035ab439ea · outbound

This paper cites TransUNet: Rethinking the U-Net architecture design for medical image segmentation through the lens of transformers[J].

Subspecialty-Specific Foundation Model for Intelligent Gastrointestinal Pathology TransUNet: Rethinking the U-Net architecture design for medical image segmentation through the lens of transformers[J]

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:26:41.270884Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T13:26:38.878287Z digest=sha256:e37ce1327a567817890ca58fc62ce4a067118611d79ff83e2ec63fe6746eba46

Observation 1aa8e5f6-0347-4b53-a41c-ea3f99dd7b24 · outbound

This paper cites Clinical and pathological staging of gastric cancer: Current perspectives and implications[J].

Subspecialty-Specific Foundation Model for Intelligent Gastrointestinal Pathology Clinical and pathological staging of gastric cancer: Current perspectives and implications[J]

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:26:41.077057Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T13:26:38.973291Z digest=sha256:0988ce300b080d31fb99b515b5a9a185342eddb4556eb08d2db6e89d6d55ffde

Observation 6e4a3ccb-b3e5-434e-be24-368a8b0a9038 · outbound

This paper cites SimpleShot: Revisiting Nearest-Neighbor Classification for Few-Shot Learning.

Subspecialty-Specific Foundation Model for Intelligent Gastrointestinal Pathology SimpleShot: Revisiting Nearest-Neighbor Classification for Few-Shot Learning

Reference 52

Resolution
unresolved
no resolver link, observed 2026-08-07T13:26:39.070025Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:26:39.070025Z digest=sha256:47b613973e75bc0e7d4372a6b8ed9cc6927c57f8ea2ac38900d534434355414b

Observation fc7c681e-0a0d-43a5-bafa-4173d8830bec · outbound

This paper cites tumor" ROI, we selected the top N₁ ROIs withthehighestclassificationconfidenceforthe.

Subspecialty-Specific Foundation Model for Intelligent Gastrointestinal Pathology tumor" ROI, we selected the top N₁ ROIs withthehighestclassificationconfidenceforthe

Reference 53

Resolution
verified exact
raw_fallback, observed 2026-08-07T13:26:39.896012Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T13:26:39.160493Z digest=sha256:2f3555aaf46bcdccfbf0a9e41a652167dc72fb4e8cb6c4fbed62e07a75d9cc1a

Observation 1c403314-dc69-417b-b770-e86e64b52866 · outbound

This paper cites An empirical study of training self-supervised vision transformers[C]//Proceedings of the IEEE/CVF international conference on computer vision.2021:9640–9649.

Subspecialty-Specific Foundation Model for Intelligent Gastrointestinal Pathology An empirical study of training self-supervised vision transformers[C]//Proceedings of the IEEE/CVF international conference on computer vision.2021:9640–9649

Reference 54

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:26:40.907567Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T13:26:39.274723Z digest=sha256:07e8f2646901de0dee4baa096ff76d48201b422db64397ac1a0d4344570f076b

Observation 5befb3c5-3480-4260-ae2d-1e391d59d6ae · outbound

This paper cites Data-efficient and weakly supervised computational pathology on whole-slide images[J].

Subspecialty-Specific Foundation Model for Intelligent Gastrointestinal Pathology Data-efficient and weakly supervised computational pathology on whole-slide images[J]

Reference 55

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:26:40.664675Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T13:26:39.355591Z digest=sha256:1f7e332a748301ad7b82e2a2fdc27c9eb50bf87a596a6885b9c8809ecb9b223a

Observation e6fd67ba-eb5d-401e-b899-74c52ca20c28 · outbound

This paper cites Transmil: Transformer based correlated multiple instance learning for whole slide image classification[J].

Subspecialty-Specific Foundation Model for Intelligent Gastrointestinal Pathology Transmil: Transformer based correlated multiple instance learning for whole slide image classification[J]

Reference 56

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:26:40.460848Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T13:26:39.454591Z digest=sha256:f6c7c800cf06ce0abe959198df79dcd2cc5cce5c8cc95ded1ef89e3c459a4634

Observation 799b0ca1-baac-49a9-a9d7-d733e27201b3 · outbound

This paper cites an unresolved cited work.

Subspecialty-Specific Foundation Model for Intelligent Gastrointestinal Pathology Unresolved cited work

Reference 57

Resolution
unresolved
raw_fallback, observed 2026-08-07T13:26:40.223907Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T13:26:39.559745Z digest=sha256:25bb2e838850d8d3afc9acbaad6fdab013b3d4e7bbbb8046a39d7c85e381df59

Observation ef2dbc81-fb6a-476d-82dd-72cc05abdfe9 · outbound

This paper cites CoCa: Contrastive Captioners are Image-Text Foundation Models.

Subspecialty-Specific Foundation Model for Intelligent Gastrointestinal Pathology CoCa: Contrastive Captioners are Image-Text Foundation Models

Reference 60

Resolution
unresolved
no resolver link, observed 2026-08-07T13:26:39.674919Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:26:39.674919Z digest=sha256:e475850c1f86a3ae00ef3bf8c64247c0b4cb580b822e67466997e5ecf9582d3a

Pith citing papers

Observation 21689152-bcd0-4685-811d-abe6117bd244 · inbound

Beyond ViT Tokens: Masked-Diffusion Pretrained Convolutional Pathology Foundation Model for Cell-Level Dense Prediction cites this paper.

Beyond ViT Tokens: Masked-Diffusion Pretrained Convolutional Pathology Foundation Model for Cell-Level Dense Prediction Subspecialty-Specific Foundation Model for Intelligent Gastrointestinal Pathology

Reference 16

Resolution
verified exact
arxiv_id, observed 2026-05-12T08:36:24.494491Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-12T00:58:28.390860Z digest=sha256:994f192b9d14c5613a04b96452a62073361420b0de6c73a5a344ea8cb48dfeec