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Paper Citation Record · LEDGER

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

As of 10 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 2026-08-10T06:31:04.303077+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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-07-11T21:16:48.107120Z digest=sha256:3163c13cb704f347bc1099bb97bb1db095ac5dd9a7ad6c4566ab3e8a15d216f6

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=sha256:521b426c3864520d17cd61a098428eb5d40c094d17fb7119ebcf03147b5d4080

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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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=sha256:6f6441aec4c71e526d04b801766799ab0b38a563276e862b8e1337e05cf5d92e

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=sha256:5441eceb5db8496277daf6e545f25244e10f5c4f0856bf0fa3bb752fdedf536c

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=sha256:30e9a2c74c8c04eabf78109832d853d00cf4c0ccfc46317defeee008fd6e8659

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

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=sha256:688ead943795527d83b132713f2c725e419b105177783453e2fcf93d4a10623a

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:b77885c4aa90df0f08c94f7b914b416701734dbfc20387049d5fd89885382e27

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:fdf2b50d6561a5a220e96c211431c6e93289286924e1ad6d2c8ef5f8fb17ed07

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

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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=sha256:332687a93dad80de42aee41751a14240c14feae73c2b7fd4effaced5a798790a

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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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=sha256:1bf6823fb98fdc92b62baf081b081ca00aeba79af4a879af294ab9f556b959df

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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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=sha256:24600a493c7feb281fff9f9d232158ea0013e0f840adfa42fd725bffac42f7a8

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:aaa26c6c9f215b52f94f6edd000faae8516122af30a5bd318880e485f53eec8b

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

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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=sha256:581ec540ceb2bdce53e1786fe7c4efc099dd488eafe8e079da8ce59cd13794d5

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=sha256:5a5cb66664be87dea328fe04d3021bace6aee37991129562598f52c8b0f7aa21

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=sha256:1f325476b707e285bdb350d988d7f4f1bc67a1c150bc15e78ece3c31c241cb16

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-11T21:16:48.107120Z digest=sha256:dc8a665d9791882375e782cc3a9351310d60c23bac2db30b0964bee8f5e9aac9

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
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:aaff90e5228d23e97536c93a02242552f8381863f315834310a5a1c15706f619

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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unresolved
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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=sha256:9a23808130210be8b631e6fa58e1ab50724852f33c753c4f136d041034e95132

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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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=sha256:9f50497a4f936981e1043fe9f6812c99b8b90796b92c64e77aa7f8d604697571

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

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:ae325c64be596de4ca3d91ac5f56178745678662ed0ead669bf2654265abea44

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

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=sha256:5473fcedbc521d5d145231862db0299612b24ff4a0a72f3a804b5241a0fad7db

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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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=sha256:8f8547689822fc69c3002dd1d30649ae4bc21083ce0452f8abb556fb86e88db0

Pith citing papers

No inbound Pith citation observations are available.