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Paper Citation Record · LEDGER

FedProIn: Mitigating Client Drift for Learnable Prototypes in Federated Medical Imaging

As of 7 August 2026, this Paper Citation Record lists 22 of 22 outbound references and 0 inbound Pith citation observations for arXiv:2607.04158.

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

pith.paper-citation-record.v1
2607.04158 v1

Coverage vector

measured 22 of 22 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-07-11T21:16:48.107120Z

measured 22 of 22 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+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

22 of 22 outbound references displayed

  • verified exact1
  • verified fuzzy0
  • unresolved21
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 549b2c1c-0d09-4770-8924-1320b90ed4d9 · outbound

This paper cites Pattern Recognition151, 110424 (2024).

FedProIn: Mitigating Client Drift for Learnable Prototypes in Federated Medical Imaging Pattern Recognition151, 110424 (2024)

Reference 1

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verified exact
arxiv_id, observed 2026-07-11T21:18:17.773206Z

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.

source=pdf_text observed=2026-07-11T21:16:48.107120Z digest=sha256:e11682dfc511ed375e38ad59fd8ef6564fea6d56d064aa299a2da7d098571b6a

Observation fc7c8e0a-e64f-4554-ae2c-0a293e914005 · outbound

This paper cites In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp.

FedProIn: Mitigating Client Drift for Learnable Prototypes in Federated Medical Imaging In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp

Reference 2

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-11T21:16:48.107120Z digest=sha256:4b1149a4b57bca0a5b3ed7387742f38a74382a9badaff1cbb538ee29b2d350d3

Observation 39811da5-4cb5-4e0e-9bb9-cf2868a61b1d · outbound

This paper cites In: 2022 21st ACM/IEEE Inter- national Conference on Information Processing in Sensor Networks (IPSN), Milano, Italy, pp.

FedProIn: Mitigating Client Drift for Learnable Prototypes in Federated Medical Imaging In: 2022 21st ACM/IEEE Inter- national Conference on Information Processing in Sensor Networks (IPSN), Milano, Italy, pp

Reference 3

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Unavailable: canonical work link unavailable.

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Observation e11fa34d-dd9e-4418-a84c-f155a7f233d4 · outbound

This paper cites an unresolved cited work.

FedProIn: Mitigating Client Drift for Learnable Prototypes in Federated Medical Imaging Unresolved cited work

Reference 4

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no resolver link, observed 2026-07-11T21:16:48.107120Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-11T21:16:48.107120Z digest=sha256:3c2311bd60f5b879103da9c1bdfe063700884b3156cd0e8586c4746dd3db75c9

Observation 1db0b17e-94d2-448e-8c56-8e067b0b3187 · outbound

This paper cites https://gdpr-info.eu/, last accessed 2026/01/25.

FedProIn: Mitigating Client Drift for Learnable Prototypes in Federated Medical Imaging https://gdpr-info.eu/, last accessed 2026/01/25

Reference 5

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-11T21:16:48.107120Z digest=sha256:8f56421a3f4eb6afcb0a22a405ac11b5e4b2719effa25466cbf8f37712d552fe

Observation d562064e-3e49-43f5-b0d1-3d30a248e62d · outbound

This paper cites In: Proceedings of the 20th International Conference on Artificial Intelligence and Statistics (AISTATS), pp.

FedProIn: Mitigating Client Drift for Learnable Prototypes in Federated Medical Imaging In: Proceedings of the 20th International Conference on Artificial Intelligence and Statistics (AISTATS), pp

Reference 6

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no resolver link, observed 2026-07-11T21:16:48.107120Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-11T21:16:48.107120Z digest=sha256:cbf25c3c57805871c5b4c70ce78b07aa192b7f5fb8e769bf0549b23126d6dfee

Observation 9fb74201-be08-430d-94b5-2bf8c6c332b1 · outbound

This paper cites Federated Optimization in Heterogeneous Networks.

FedProIn: Mitigating Client Drift for Learnable Prototypes in Federated Medical Imaging Federated Optimization in Heterogeneous Networks

Reference 7

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-11T21:16:48.107120Z digest=sha256:c7a26bb5ba38962f41fd2c7c10fb82cb45097302eefbe29700545482f0babdb2

Observation d6ace260-5c32-4473-897e-0a5d84f51335 · outbound

This paper cites In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp.

FedProIn: Mitigating Client Drift for Learnable Prototypes in Federated Medical Imaging In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp

Reference 8

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no resolver link, observed 2026-07-11T21:16:48.107120Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-11T21:16:48.107120Z digest=sha256:0e7a98dad9c67d1b26bbbcdc6c6599b1dfe2f0ce6737c03d8e31fb7647b8cd27

Observation 967d8278-409c-439c-869d-879f73b4e3fa · outbound

This paper cites In: Proceedings of the AAAI Conference on Artificial Intelligence, vol.

FedProIn: Mitigating Client Drift for Learnable Prototypes in Federated Medical Imaging In: Proceedings of the AAAI Conference on Artificial Intelligence, vol

Reference 9

Resolution
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no resolver link, observed 2026-07-11T21:16:48.107120Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-11T21:16:48.107120Z digest=sha256:9602caeda1974328b3bbcd13037ef7fd66f796ae77b8c1e8ce7d89ba27a9a301

Observation caf943df-cd34-4b2e-9d59-aec41e2525e4 · outbound

This paper cites Future Generation Computer Systems 143, 93–104 (2023).

FedProIn: Mitigating Client Drift for Learnable Prototypes in Federated Medical Imaging Future Generation Computer Systems 143, 93–104 (2023)

Reference 10

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-11T21:16:48.107120Z digest=sha256:1720201d97afc50ee2bf6a113de0e228d0e3d065a0aeddc409c332ad941243c1

Observation 896f7dcb-f763-43e6-a498-879b13c6b9b8 · outbound

This paper cites an unresolved cited work.

FedProIn: Mitigating Client Drift for Learnable Prototypes in Federated Medical Imaging Unresolved cited work

Reference 11

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no resolver link, observed 2026-07-11T21:16:48.107120Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-11T21:16:48.107120Z digest=sha256:a2c1c6832a3aec953706be18dc6c18afe2d81bf56837838d701da61661283e83

Observation 223ae131-b70d-4dfc-944b-fd6f5a228aa9 · outbound

This paper cites In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR 2023), pp.

FedProIn: Mitigating Client Drift for Learnable Prototypes in Federated Medical Imaging In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR 2023), pp

Reference 12

Resolution
unresolved
no resolver link, observed 2026-07-11T21:16:48.107120Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-11T21:16:48.107120Z digest=sha256:8610830e29593dbb0227119ff82870a182fb5ddca8079958db5e687a855fa257

Observation 9a46a8e7-76c7-4326-b4f1-7e455c5bb161 · outbound

This paper cites In: Advances in Neural Information Processing Systems, vol.

FedProIn: Mitigating Client Drift for Learnable Prototypes in Federated Medical Imaging In: Advances in Neural Information Processing Systems, vol

Reference 13

Resolution
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-11T21:16:48.107120Z digest=sha256:6ff2e721b2e40d2c5feba14c1f5cc67ab57d596707a4e6e6b7284bfa6eae3083

Observation 5f13793a-0d62-47aa-810c-e3e296eaefb5 · outbound

This paper cites Scientific Data5(1), 1–9 (2018) 10 Harsh Kumar, Tarun Kumar Garg, and Vaanathi Sundaresan.

FedProIn: Mitigating Client Drift for Learnable Prototypes in Federated Medical Imaging Scientific Data5(1), 1–9 (2018) 10 Harsh Kumar, Tarun Kumar Garg, and Vaanathi Sundaresan

Reference 14

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unresolved
no resolver link, observed 2026-07-11T21:16:48.107120Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-11T21:16:48.107120Z digest=sha256:25b6357163b03785c666054c5e595712143a45bee3006e943ec8c43319470592

Observation 64defacd-5714-4a91-a213-8bbea641683b · outbound

This paper cites an unresolved cited work.

FedProIn: Mitigating Client Drift for Learnable Prototypes in Federated Medical Imaging Unresolved cited work

Reference 15

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unresolved
no resolver link, observed 2026-07-11T21:16:48.107120Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-11T21:16:48.107120Z digest=sha256:d94678ca048918dfd912f4ed2128ce5156a0a3b3cf4c6cbefff66ea7d4d5a7ad

Observation 272e7839-9761-42a9-a218-583e04c3d39f · outbound

This paper cites In: III, H.D., Singh, A.

FedProIn: Mitigating Client Drift for Learnable Prototypes in Federated Medical Imaging In: III, H.D., Singh, A

Reference 16

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no resolver link, observed 2026-07-11T21:16:48.107120Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-11T21:16:48.107120Z digest=sha256:42e431d6b671c34f829332932d281b11c79a34a331cba92854c4aa0a491b54aa

Observation ab2e38cd-ebb9-4e79-b653-90cb42cc9c8e · outbound

This paper cites In: International Confer- ence on Learning Representations (ICLR) (2021).

FedProIn: Mitigating Client Drift for Learnable Prototypes in Federated Medical Imaging In: International Confer- ence on Learning Representations (ICLR) (2021)

Reference 17

Resolution
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-11T21:16:48.107120Z digest=sha256:17aaea39230a2236bb7a3b6f7269417159e8b15929980f931799f2954840b624

Observation 84e02d7f-ea52-4865-9a95-c1f6c5d78f28 · outbound

This paper cites In: Koyejo, S., Mohamed, S., Agarwal, A., Belgrave, D., Cho, K., Oh, A.

FedProIn: Mitigating Client Drift for Learnable Prototypes in Federated Medical Imaging In: Koyejo, S., Mohamed, S., Agarwal, A., Belgrave, D., Cho, K., Oh, A

Reference 18

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-11T21:16:48.107120Z digest=sha256:b3b2f3c85663501bc47a5374cca34f37786a2d2fa68b9c1f135133f5f38fde6d

Observation a93c669b-62d8-4e72-828e-33588d821b0d · outbound

This paper cites an unresolved cited work.

FedProIn: Mitigating Client Drift for Learnable Prototypes in Federated Medical Imaging Unresolved cited work

Reference 19

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-11T21:16:48.107120Z digest=sha256:96c18416aafcf3cd8f3b0d20cca4665047fa8471aed14961afacbeb98dab6d24

Observation 8c4a942e-46cd-495c-a96d-3e49ca97891b · outbound

This paper cites In: 2009 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp.

FedProIn: Mitigating Client Drift for Learnable Prototypes in Federated Medical Imaging In: 2009 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp

Reference 20

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unresolved
no resolver link, observed 2026-07-11T21:16:48.107120Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-11T21:16:48.107120Z digest=sha256:9f08e8fcb3c0b8c3981903dd94cf1a1fe84552acdfcae255fc4e4d86b0551179

Observation edfbd54f-0da7-4f1c-a40e-0e359f1ed8be · outbound

This paper cites Adam: A Method for Stochastic Optimization.

FedProIn: Mitigating Client Drift for Learnable Prototypes in Federated Medical Imaging Adam: A Method for Stochastic Optimization

Reference 21

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-11T21:16:48.107120Z digest=sha256:7d959f9fad7bc693e54ab13db4c52bfcda4d7e510aee99477e39b9d8242a62ed

Observation 49ad2982-c6b1-4de7-8949-0353d75c5b1e · outbound

This paper cites Advances in neural information processing systems32, 2019.

FedProIn: Mitigating Client Drift for Learnable Prototypes in Federated Medical Imaging Advances in neural information processing systems32, 2019

Reference 22

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-11T21:16:48.107120Z digest=sha256:f848cb6a164f5c005486bc53df17b1e391d671d3645e06367520dda6a2ab8e55

Pith citing papers

No inbound Pith citation observations are available.