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Paper Citation Record · LEDGER

Enhancing breast cancer detection on screening mammogram using self-supervised learning and a hybrid deep model of Swin Transformer and Convolutional Neural Network

As of 18 August 2026, this Paper Citation Record lists 36 of 36 outbound references and 0 inbound Pith citation observations for arXiv:2504.19888.

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

pith.paper-citation-record.v1
2504.19888 v1

Coverage vector

measured 36 of 36 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-16T05:44:15.765397Z

measured 36 of 36 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

36 of 36 outbound references displayed

  • verified exact1
  • verified fuzzy14
  • unresolved21
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 6c75fe9c-1449-4492-b373-4a18cacf2ee4 · outbound

This paper cites an unresolved cited work.

Enhancing breast cancer detection on screening mammogram using self-supervised learning and a hybrid deep model of Swin Transformer and Convolutional Neural Network Unresolved cited work

Reference 1

Resolution
unresolved
raw_fallback, observed 2026-08-16T05:44:16.177265Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-16T05:44:15.639011Z digest=sha256:05e75502a6a2c2d92f3eb78e0e4b7476317b8c5edfb729435820caf49d8c1310

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T05:44:16.167431Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-16T05:44:15.643379Z digest=sha256:e861366b9478a56895cfe5996323cefab4f902f012c579439e999b8b591dc3b7

Observation 5bc2dc3e-957b-4838-a0a3-c6025ae207d6 · outbound

This paper cites an unresolved cited work.

Enhancing breast cancer detection on screening mammogram using self-supervised learning and a hybrid deep model of Swin Transformer and Convolutional Neural Network Unresolved cited work

Reference 3

Resolution
unresolved
raw_fallback, observed 2026-08-16T05:44:16.156590Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-16T05:44:15.647008Z digest=sha256:fc3bdd50b4dee1304f78b93fa5e486ee49bf1d3ac2b7e363d3c0ab2953e4b340

Observation 77ac5d8a-0c69-4eee-aea9-1dc7ee977bce · outbound

This paper cites an unresolved cited work.

Enhancing breast cancer detection on screening mammogram using self-supervised learning and a hybrid deep model of Swin Transformer and Convolutional Neural Network Unresolved cited work

Reference 4

Resolution
unresolved
raw_fallback, observed 2026-08-16T05:44:16.146016Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-16T05:44:15.650578Z digest=sha256:ddea23f1455f3a9733f5298ab84f26f68664df85290656eb224bae2aa72e6574

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T05:44:16.135780Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-16T05:44:15.654491Z digest=sha256:ec266d6423a95cffa37baecd9ad38571dd55b047e2760ae03b9bbeef099288fc

Observation 7674fd7d-2887-4367-bd29-63c0231f3e4a · outbound

This paper cites an unresolved cited work.

Enhancing breast cancer detection on screening mammogram using self-supervised learning and a hybrid deep model of Swin Transformer and Convolutional Neural Network Unresolved cited work

Reference 6

Resolution
unresolved
raw_fallback, observed 2026-08-16T05:44:16.125583Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-16T05:44:15.658286Z digest=sha256:1fe83b2025ad9ef79cb530837feea8bc37164709b00c4707ef7c731a1c48692e

Observation 80568a0d-c750-4f3a-97f4-37399201e7c8 · outbound

This paper cites an unresolved cited work.

Enhancing breast cancer detection on screening mammogram using self-supervised learning and a hybrid deep model of Swin Transformer and Convolutional Neural Network Unresolved cited work

Reference 7

Resolution
unresolved
raw_fallback, observed 2026-08-16T05:44:16.115312Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-16T05:44:15.662375Z digest=sha256:117ff9815837cb82f5d7c4ccf557acb364aeee03b7ee1b3c89b0305f354e267e

Observation 77f62841-9a07-46aa-8a89-401c30793438 · outbound

This paper cites Schaffter, D.

Enhancing breast cancer detection on screening mammogram using self-supervised learning and a hybrid deep model of Swin Transformer and Convolutional Neural Network Schaffter, D

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T05:44:16.104437Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-16T05:44:15.665900Z digest=sha256:e5b5389d5af2ee836fd86c2fb7f28ed10a0b42ec27cec8e25c0046068e6980bf

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T05:44:16.093912Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-16T05:44:15.669352Z digest=sha256:9c853702b885c90794473b52f01febf7faad297f71966bd3bf6149aa73fd83cb

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T05:44:16.082903Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-16T05:44:15.672876Z digest=sha256:616d48d71757d50d05bd3157201af01223badcb2a647cf0b3ad24d464624d83a

Observation 2b73cae7-6430-44fd-babe-f526be6fc386 · outbound

This paper cites an unresolved cited work.

Enhancing breast cancer detection on screening mammogram using self-supervised learning and a hybrid deep model of Swin Transformer and Convolutional Neural Network Unresolved cited work

Reference 11

Resolution
unresolved
raw_fallback, observed 2026-08-16T05:44:16.071062Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-16T05:44:15.676343Z digest=sha256:051b68e043d71c2a8b98608cf734bd27d09596b91a14a55414d938429bc5bf4c

Observation e0e5ddfd-9816-4e83-af40-8a65bebb9ccd · outbound

This paper cites an unresolved cited work.

Enhancing breast cancer detection on screening mammogram using self-supervised learning and a hybrid deep model of Swin Transformer and Convolutional Neural Network Unresolved cited work

Reference 12

Resolution
unresolved
raw_fallback, observed 2026-08-16T05:44:16.060009Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-16T05:44:15.679660Z digest=sha256:4d88d95c5df835e6666a92c8c79c8b2b46958983b066e2ec9dff9ff95348bca8

Observation 48155727-85d6-4032-91bc-24a7e9d284df · outbound

This paper cites an unresolved cited work.

Enhancing breast cancer detection on screening mammogram using self-supervised learning and a hybrid deep model of Swin Transformer and Convolutional Neural Network Unresolved cited work

Reference 13

Resolution
unresolved
raw_fallback, observed 2026-08-16T05:44:16.048272Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-16T05:44:15.683118Z digest=sha256:afe930b9fd403d3f2fe8da69d3bb16a8f85ab731a57feca298a2f11d20c501c1

Observation cfa5b1be-e976-4c71-b5a9-ef9cf66420fd · outbound

This paper cites an unresolved cited work.

Enhancing breast cancer detection on screening mammogram using self-supervised learning and a hybrid deep model of Swin Transformer and Convolutional Neural Network Unresolved cited work

Reference 14

Resolution
unresolved
raw_fallback, observed 2026-08-16T05:44:16.036659Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-16T05:44:15.686535Z digest=sha256:82bd8960765cb8230f5c971195e963d37dd7d164b778c21812ffca8e50909ae7

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T05:44:16.025972Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-16T05:44:15.690178Z digest=sha256:71863bc3090cadbbb9e4a60456e90326aeb89d2015c6aa22a3e031ad55ad9865

Observation 925ec591-f7f2-4018-a125-73baab45a200 · outbound

This paper cites Rangarajan, A.

Enhancing breast cancer detection on screening mammogram using self-supervised learning and a hybrid deep model of Swin Transformer and Convolutional Neural Network Rangarajan, A

Reference 16

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T05:44:16.014075Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-16T05:44:15.693810Z digest=sha256:18a175026e21a5db290fb26bdb42a7bb622343eea8555a48631fff723ffdab47

Observation b4c97eca-ac5e-43de-9aae-a0d731bb4ed0 · outbound

This paper cites an unresolved cited work.

Enhancing breast cancer detection on screening mammogram using self-supervised learning and a hybrid deep model of Swin Transformer and Convolutional Neural Network Unresolved cited work

Reference 17

Resolution
unresolved
raw_fallback, observed 2026-08-16T05:44:16.003638Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-16T05:44:15.697345Z digest=sha256:bcae21948e872e43905a83bc9c9bd41e35268b3d10d84799d561029483c6960e

Observation af26d5fa-29d3-4ae0-9509-4c0597b108e0 · outbound

This paper cites an unresolved cited work.

Enhancing breast cancer detection on screening mammogram using self-supervised learning and a hybrid deep model of Swin Transformer and Convolutional Neural Network Unresolved cited work

Reference 18

Resolution
unresolved
raw_fallback, observed 2026-08-16T05:44:15.992041Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-16T05:44:15.700857Z digest=sha256:113f6211fd3a7c39dcb0c07d314e91456199fcca84942a3aeb7223b5cc63c3d7

Reference 19

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T05:44:15.981483Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-16T05:44:15.704235Z digest=sha256:df77f68260deb14e37ec3cb98d9d492f09b5a898b50faba1ad9395a213606946

Observation c2a68110-0d75-4a1c-8870-3a2a403f8872 · outbound

This paper cites an unresolved cited work.

Enhancing breast cancer detection on screening mammogram using self-supervised learning and a hybrid deep model of Swin Transformer and Convolutional Neural Network Unresolved cited work

Reference 20

Resolution
unresolved
raw_fallback, observed 2026-08-16T05:44:15.970558Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-16T05:44:15.707609Z digest=sha256:67a420c0ca03274cf5e3766b6a6d83c60ea1f44174d903305fc77eb8e4db7f0f

Reference 21

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T05:44:15.959060Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-16T05:44:15.711209Z digest=sha256:6c4c7138464015e35ae5eff01fe8611744f24ae4237805130bd3d94ce0e7625d

Reference 22

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T05:44:15.948703Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-16T05:44:15.714491Z digest=sha256:34115e3c71eb2229765c4f84e3ae2a98e4816c4fcd0f37c1f7882453562d6bb0

Observation d7ae4e06-d3ee-4f6c-a930-2450346d26a0 · outbound

This paper cites Efficient Self-supervised Vision Transformers for Representation Learning.

Enhancing breast cancer detection on screening mammogram using self-supervised learning and a hybrid deep model of Swin Transformer and Convolutional Neural Network Efficient Self-supervised Vision Transformers for Representation Learning

Reference 23

Resolution
unresolved
no resolver link, observed 2026-08-16T05:44:15.718289Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T05:44:15.718289Z digest=sha256:b7c9a141e2e13330c2d400e9d2aacec7acc2aefddebe46aa6af958154b082387

Reference 24

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T05:44:15.938415Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-16T05:44:15.721822Z digest=sha256:9ef72441d16aee940ba1598cf2a8824e2df9f2b6c937d418fa902cc8f8001d81

Reference 25

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T05:44:15.927759Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-16T05:44:15.724897Z digest=sha256:3c0fb60a8d22213082acb7241fa1fe4f6360bf2ee8f2ed73a191d2071c8f43ed

Observation 0114a42c-2d27-4783-a095-1b5e88cd02e5 · outbound

This paper cites an unresolved cited work.

Enhancing breast cancer detection on screening mammogram using self-supervised learning and a hybrid deep model of Swin Transformer and Convolutional Neural Network Unresolved cited work

Reference 26

Resolution
unresolved
raw_fallback, observed 2026-08-16T05:44:15.917182Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-16T05:44:15.728021Z digest=sha256:fcf37f52d8e65e7ec18b32ece5873aeceab6414f523433a7b3b3675e0c75fd86

Reference 27

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T05:44:15.906660Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-16T05:44:15.731659Z digest=sha256:98d5ab4c61f29174b7ac6cac4d8cbcb72e207e330d0f6f77114b5d4b2ba59b4b

Observation f1f16036-5360-4ea8-9cd9-b2f37677ff44 · outbound

This paper cites an unresolved cited work.

Enhancing breast cancer detection on screening mammogram using self-supervised learning and a hybrid deep model of Swin Transformer and Convolutional Neural Network Unresolved cited work

Reference 28

Resolution
unresolved
raw_fallback, observed 2026-08-16T05:44:15.895548Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-16T05:44:15.735013Z digest=sha256:e93e3d1fdd002802aecd8a16aaefccc511a2cae10716f07cf20d2427f500d889

Observation 353f6c5b-887c-4827-85ad-57bef4fd46c5 · outbound

This paper cites End-to-end Training for Whole Image Breast Cancer Diagnosis using An All Convolutional Design.

Enhancing breast cancer detection on screening mammogram using self-supervised learning and a hybrid deep model of Swin Transformer and Convolutional Neural Network End-to-end Training for Whole Image Breast Cancer Diagnosis using An All Convolutional Design

Reference 29

Resolution
verified exact
local_arxiv, observed 2026-08-16T05:44:15.811308Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-16T05:44:15.739027Z digest=sha256:10e63c3fdb49b69358b2a7f890ab51d02fe59a315e95237e9bd6eb0ac4177c57

Observation 31854f39-414f-48b8-8ffa-d2769d6ca41c · outbound

This paper cites an unresolved cited work.

Enhancing breast cancer detection on screening mammogram using self-supervised learning and a hybrid deep model of Swin Transformer and Convolutional Neural Network Unresolved cited work

Reference 30

Resolution
unresolved
raw_fallback, observed 2026-08-16T05:44:15.883996Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-16T05:44:15.744074Z digest=sha256:800315ad539ce66a20d1c355d2ca0bcbaabd26a3887a43a96f6a00969d70c0cc

Observation 053974d6-932d-416c-926d-9fe2c59fae45 · outbound

This paper cites an unresolved cited work.

Enhancing breast cancer detection on screening mammogram using self-supervised learning and a hybrid deep model of Swin Transformer and Convolutional Neural Network Unresolved cited work

Reference 31

Resolution
unresolved
raw_fallback, observed 2026-08-16T05:44:15.873398Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-16T05:44:15.747519Z digest=sha256:2dabd8ab0e55179d1e95f54d745089fa05428741f9d83a522230c25e7ac2e30f

Observation 73c51b5d-6893-4ce0-84e5-35245668af5c · outbound

This paper cites an unresolved cited work.

Enhancing breast cancer detection on screening mammogram using self-supervised learning and a hybrid deep model of Swin Transformer and Convolutional Neural Network Unresolved cited work

Reference 32

Resolution
unresolved
raw_fallback, observed 2026-08-16T05:44:15.862177Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-16T05:44:15.750924Z digest=sha256:c0efcadca21ef222ab8250106e6d31f77e75220157e91d83ef55874e75108943

Reference 33

Resolution
unresolved
no resolver link, observed 2026-08-16T05:44:15.754299Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T05:44:15.754299Z digest=sha256:1e78dc40f9835408b7772b214c966085d8b877463d60057bc887f5a7cb36e29a

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T05:44:15.851325Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-16T05:44:15.758159Z digest=sha256:be44dc24cda5b6af06a4791c0a7c6aad69443cbee281a39d805a1eff7efc0470

Observation 331d0159-7dbb-4299-953d-cd328e7eab9b · outbound

This paper cites an unresolved cited work.

Enhancing breast cancer detection on screening mammogram using self-supervised learning and a hybrid deep model of Swin Transformer and Convolutional Neural Network Unresolved cited work

Reference 35

Resolution
unresolved
raw_fallback, observed 2026-08-16T05:44:15.839327Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-16T05:44:15.761730Z digest=sha256:a717d64a524cdb73cda740f60c8b1c236158bde6a5abdf3bab12504c07411893

Observation 6f6beecc-4caa-44e3-affa-f1fb142089ed · outbound

This paper cites write newline.

Enhancing breast cancer detection on screening mammogram using self-supervised learning and a hybrid deep model of Swin Transformer and Convolutional Neural Network write newline

Reference 36

Resolution
unresolved
no resolver link, observed 2026-08-16T05:44:15.765397Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T05:44:15.765397Z digest=sha256:a21eae1d0682fac431d394596a8ce37712d7998bed738d2f41b4c9db1302e2ee

Pith citing papers

No inbound Pith citation observations are available.