Paper Citation Record · LEDGER

Decoding Federated Learning: The FedNAM+ Conformal Revolution

As of 23 August 2026, this Paper Citation Record lists 37 of 37 outbound references and 1 inbound Pith citation observation for arXiv:2506.17872.

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

pith.paper-citation-record.v1
2506.17872 v2

Coverage vector

measured 37 of 37 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T19:02:10.319297Z

measured 38 of 38 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-23T06:30:58.430688+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T18:33:29.185714Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-06T18:33:32.005505Z

Reference resolution

37 of 37 outbound references displayed

verified exact1
verified fuzzy26
unresolved9
parse uncertain0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 22a115a5-beca-4944-acf2-7050367eed04 · outbound

This paper cites Neural additive models: Interpretable machine learning with neural nets.

Decoding Federated Learning: The FedNAM+ Conformal Revolution Neural additive models: Interpretable machine learning with neural nets

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:02:11.031501Z

Source-reported events for the cited work

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Observation 975ea615-52d2-4c85-ab22-2bbfdfc96ba5 · outbound

This paper cites Handling privacy-sensitive medical data with federated learning: challenges and future directions.

Decoding Federated Learning: The FedNAM+ Conformal Revolution Handling privacy-sensitive medical data with federated learning: challenges and future directions

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:02:11.016545Z

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Observation 595678e9-136e-4d02-bce4-7a970eb35a33 · outbound

This paper cites FedMM-X: A Trustworthy and Interpretable Framework for Federated Multi-Modal Learning in Dynamic Environments.

Decoding Federated Learning: The FedNAM+ Conformal Revolution FedMM-X: A Trustworthy and Interpretable Framework for Federated Multi-Modal Learning in Dynamic Environments

Reference 3

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Observation 8eb93f5f-1a96-4745-a3c0-f80de375b79c · outbound

This paper cites Building communication efficient asynchronous peer-to-peer federated llms with blockchain.

Decoding Federated Learning: The FedNAM+ Conformal Revolution Building communication efficient asynchronous peer-to-peer federated llms with blockchain

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:02:10.978919Z

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Observation e81a2824-6362-414f-b3c8-e93325a8ec0c · outbound

This paper cites Principal uncertainty quantifica- tion with spatial correlation for image restoration problems.

Decoding Federated Learning: The FedNAM+ Conformal Revolution Principal uncertainty quantifica- tion with spatial correlation for image restoration problems

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:02:10.964535Z

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Observation 5ffccb9f-8d8b-41e5-af65-e61e7cdee2cb · outbound

This paper cites Cipahr: A secure federated framework for healthcare.

Decoding Federated Learning: The FedNAM+ Conformal Revolution Cipahr: A secure federated framework for healthcare

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:02:10.951075Z

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Observation cc1e4288-0969-471a-a861-7ffc14400d8f · outbound

This paper cites Differentially Private Federated Learning: A Client Level Perspective.

Decoding Federated Learning: The FedNAM+ Conformal Revolution Differentially Private Federated Learning: A Client Level Perspective

Reference 7

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Observation 7d3ba3d1-b791-47c7-9ba0-4e393509c766 · outbound

This paper cites AILuminate: Introducing v1.0 of the AI Risk and Reliability Benchmark from MLCommons.

Decoding Federated Learning: The FedNAM+ Conformal Revolution AILuminate: Introducing v1.0 of the AI Risk and Reliability Benchmark from MLCommons

Reference 8

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Observation 23d5723a-194a-47fa-9e70-a05d6c5f14f8 · outbound

This paper cites Chest ct-scan images dataset.

Decoding Federated Learning: The FedNAM+ Conformal Revolution Chest ct-scan images dataset

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:02:10.935335Z

Source-reported events for the cited work

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Observation 00ed11f4-fdfa-4fc1-bd7e-0e4f1cfbb2b4 · outbound

This paper cites Seman- tic uncertainty: Linguistic invariances for uncertainty esti- mation in natural language generation.

Decoding Federated Learning: The FedNAM+ Conformal Revolution Seman- tic uncertainty: Linguistic invariances for uncertainty esti- mation in natural language generation

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:02:10.903737Z

Source-reported events for the cited work

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Observation 6c0ac247-125e-4e62-8226-ac0422a9407e · outbound

This paper cites Towards Interpretable Federated Learning.

Decoding Federated Learning: The FedNAM+ Conformal Revolution Towards Interpretable Federated Learning

Reference 11

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Observation 00211dea-5b54-4cf0-a78e-5f7c9240172d · outbound

This paper cites Heterogeneous federated learning.

Decoding Federated Learning: The FedNAM+ Conformal Revolution Heterogeneous federated learning

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:02:10.879137Z

Source-reported events for the cited work

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Observation a02958a5-d089-4635-aa8d-f29bc64a47e6 · outbound

This paper cites Lopez-Ramos, Florian Leiser, Aditya Rastogi, Steven Hicks, Inga Str ¨umke, Vince I.

Decoding Federated Learning: The FedNAM+ Conformal Revolution Lopez-Ramos, Florian Leiser, Aditya Rastogi, Steven Hicks, Inga Str ¨umke, Vince I

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:02:10.863249Z

Source-reported events for the cited work

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Observation be80a0a8-6927-40fb-b134-b7db0da1e757 · outbound

This paper cites Brendan McMahan, Eider Moore, Daniel Ramage, Seth Hampson, and Blaise Aguera y Arcas.

Decoding Federated Learning: The FedNAM+ Conformal Revolution Brendan McMahan, Eider Moore, Daniel Ramage, Seth Hampson, and Blaise Aguera y Arcas

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:02:10.848495Z

Source-reported events for the cited work

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Observation e5f8c122-b3b7-4458-884d-084fb2c3c217 · outbound

This paper cites On uncertainty quantification in language models.

Decoding Federated Learning: The FedNAM+ Conformal Revolution On uncertainty quantification in language models

Reference 15

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Source-reported events for the cited work

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Observation 349ee74a-19ce-49b3-b363-4a054cb5958d · outbound

This paper cites Uncertainty quantification.

Decoding Federated Learning: The FedNAM+ Conformal Revolution Uncertainty quantification

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:02:10.815730Z

Source-reported events for the cited work

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Observation 43e5a506-06d6-4035-8e0e-cb03ad5d9351 · outbound

This paper cites Cptquant–a novel mixed precision post-training quantiza- tion techniques for large language models.

Decoding Federated Learning: The FedNAM+ Conformal Revolution Cptquant–a novel mixed precision post-training quantiza- tion techniques for large language models

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:02:10.799355Z

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Observation b3b00d45-52db-48d2-baf4-8585802d53ac · outbound

This paper cites FedNAMs: Performing Interpretability Analysis in Federated Learning Context.

Decoding Federated Learning: The FedNAM+ Conformal Revolution FedNAMs: Performing Interpretability Analysis in Federated Learning Context

Reference 18

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Observation 7340711b-b3bd-4c54-b003-53c89e64e0ff · outbound

This paper cites ”why should i trust you?”: Explaining the predictions of any classifier.

Decoding Federated Learning: The FedNAM+ Conformal Revolution ”why should i trust you?”: Explaining the predictions of any classifier

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:02:10.784262Z

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Observation ed15c129-4ce2-49da-a2c6-26e139ab27b7 · outbound

This paper cites Very deep convo- lutional networks for large-scale image recognition.

Decoding Federated Learning: The FedNAM+ Conformal Revolution Very deep convo- lutional networks for large-scale image recognition

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:02:10.765194Z

Source-reported events for the cited work

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Observation 42e9f2c6-c076-4457-91f7-d585e4e34214 · outbound

This paper cites Federated multi-task learning.

Decoding Federated Learning: The FedNAM+ Conformal Revolution Federated multi-task learning

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:02:10.745107Z

Source-reported events for the cited work

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Observation a4d393e1-ce6c-469c-9ae6-cea518651270 · outbound

This paper cites Im- proved conformalized quantile regression.

Decoding Federated Learning: The FedNAM+ Conformal Revolution Im- proved conformalized quantile regression

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:02:10.733271Z

Source-reported events for the cited work

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Observation 471a1630-bf22-4d28-a312-de8c1697dc51 · outbound

This paper cites Vision transformers for uncertainty estima- tion.

Decoding Federated Learning: The FedNAM+ Conformal Revolution Vision transformers for uncertainty estima- tion

Reference 23

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Observation 3fc7cb17-94da-4d5a-8a11-c2d745cfce1c · outbound

This paper cites Understand- ing neural abstractive summarization models via uncertainty.

Decoding Federated Learning: The FedNAM+ Conformal Revolution Understand- ing neural abstractive summarization models via uncertainty

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:02:10.721015Z

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Observation 446f9b42-7aa8-43a5-80b4-20ccfbabaec2 · outbound

This paper cites A clustered federated learn- ing method of user behavior analysis based on non-iid data.

Decoding Federated Learning: The FedNAM+ Conformal Revolution A clustered federated learn- ing method of user behavior analysis based on non-iid data

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:02:10.707357Z

Source-reported events for the cited work

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Observation d8cacf85-6c41-4689-8125-8fd9c928b4ea · outbound

This paper cites A survey of trustworthy federated learning: Issues, solutions, and challenges.

Decoding Federated Learning: The FedNAM+ Conformal Revolution A survey of trustworthy federated learning: Issues, solutions, and challenges

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:02:10.693599Z

Source-reported events for the cited work

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Observation 1391e100-2529-4eea-a997-add15853a78e · outbound

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Decoding Federated Learning: The FedNAM+ Conformal Revolution Unresolved cited work

Reference 29

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Observation e0a4a0be-d034-409d-b25d-8e63fc68327c · outbound

This paper cites • This resulted in a significant drop in interpretability and a minor decrease in accuracy, highlighting the crit- ical role of NAMs in providing explainable outcomes.

Decoding Federated Learning: The FedNAM+ Conformal Revolution • This resulted in a significant drop in interpretability and a minor decrease in accuracy, highlighting the crit- ical role of NAMs in providing explainable outcomes

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:02:10.663616Z

Source-reported events for the cited work

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Observation ba4dbca8-e3bc-4af0-b915-7852823e79e2 · outbound

This paper cites • Improper tuning led to slower convergence and re- duced accuracy, emphasizing the importance of care- ful parameter selection.

Decoding Federated Learning: The FedNAM+ Conformal Revolution • Improper tuning led to slower convergence and re- duced accuracy, emphasizing the importance of care- ful parameter selection

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:02:10.649748Z

Source-reported events for the cited work

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Observation e8ef5740-d82e-4a84-8ea1-32c13f577d4e · outbound

This paper cites Non-Clustering: • The clustering mechanism used in FedNAM+ was dis- abled, resulting in a noticeable decrease in computa- tional efficiency and a slight accuracy reduction.

Decoding Federated Learning: The FedNAM+ Conformal Revolution Non-Clustering: • The clustering mechanism used in FedNAM+ was dis- abled, resulting in a noticeable decrease in computa- tional efficiency and a slight accuracy reduction

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:02:10.635336Z

Source-reported events for the cited work

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Observation 4a645e82-bb2c-407a-b2d1-0ca4bee386fa · outbound

This paper cites • The results indicated that the chosen aggregation ap- proach in FedNAM+ provides better alignment across clients, especially in IID scenarios.

Decoding Federated Learning: The FedNAM+ Conformal Revolution • The results indicated that the chosen aggregation ap- proach in FedNAM+ provides better alignment across clients, especially in IID scenarios

Reference 33

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Observation 319ca182-d077-4f3a-97fa-7f1f66983004 · outbound

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Decoding Federated Learning: The FedNAM+ Conformal Revolution Unresolved cited work

Reference 34

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Observation 805e29f2-af8b-4849-8a96-d799d238400f · outbound

This paper cites How- ever, this approach lacks a theoretical foundation guaran- teeing its validity.

Decoding Federated Learning: The FedNAM+ Conformal Revolution How- ever, this approach lacks a theoretical foundation guaran- teeing its validity

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:02:10.573235Z

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Observation ad3c9fa2-58dc-426e-815f-4e42ed3d6b7b · outbound

This paper cites This as- sumption is inconsistent with the federated learning setting, where data is typically non-IID due to variations in local data distributions among clients.

Decoding Federated Learning: The FedNAM+ Conformal Revolution This as- sumption is inconsistent with the federated learning setting, where data is typically non-IID due to variations in local data distributions among clients

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:02:10.552049Z

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Observation 56605dd5-5c9a-4940-9f90-4bdd3c55d78d · outbound

This paper cites Conformal prediction is a well-established method for pro- viding calibrated uncertainty estimates and relies on spe- cific assumptions and methodologies.

Decoding Federated Learning: The FedNAM+ Conformal Revolution Conformal prediction is a well-established method for pro- viding calibrated uncertainty estimates and relies on spe- cific assumptions and methodologies

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:02:10.533491Z

Source-reported events for the cited work

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Observation d4fe0329-0b2b-4b72-b8d9-43fe0d43566a · outbound

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Decoding Federated Learning: The FedNAM+ Conformal Revolution Unresolved cited work

Reference 2020

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Observation 607928f7-41e6-4f91-b001-bada5af031a6 · outbound

This paper cites an unresolved cited work.

Decoding Federated Learning: The FedNAM+ Conformal Revolution Unresolved cited work

Reference 2025

Resolution: unresolved; raw_fallback, observed 2026-08-15T19:02:10.995771Z

Source-reported events for the cited work

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Pith citing papers

Observation 1b45a980-42c1-464a-b635-5d0fccdcb63b · inbound

The Trust Fabric: Decentralized Interoperability and Economic Coordination for the Agentic Web cites this paper.

The Trust Fabric: Decentralized Interoperability and Economic Coordination for the Agentic Web Decoding Federated Learning: The FedNAM+ Conformal Revolution

Reference 4

Resolution: verified exact; local_arxiv, observed 2026-08-06T18:33:32.155493Z

Source-reported events for the cited work

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