Paper Citation Record · LEDGER

Federated Evaluation and Tuning for On-Device Personalization: System Design & Applications

As of 20 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 10 inbound Pith citation observations for arXiv:2102.08503.

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

pith.paper-citation-record.v1
2102.08503 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 10 of 10 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+00:00

measured 10 of 10 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T11:09:46.609318Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-01T16:45:51.872922Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 2ec4c3e9-9da9-4d4e-8b6d-183837e0ba43 · inbound

On the Robustness of Distributed Machine Learning against Transfer Attacks cites this paper.

On the Robustness of Distributed Machine Learning against Transfer Attacks Federated Evaluation and Tuning for On-Device Personalization: System Design & Applications

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-11T12:33:25.641663Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2f6fc0e5-862e-440b-8c07-bd9d1f6f6138 · inbound

Decoding FL Defenses: Systemization, Pitfalls, and Remedies cites this paper.

Decoding FL Defenses: Systemization, Pitfalls, and Remedies Federated Evaluation and Tuning for On-Device Personalization: System Design & Applications

Reference 72

Resolution: unresolved; no resolver link, observed 2026-08-09T14:12:23.340903Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2fee7a39-6b05-49b9-a24c-7021464ecdbc · inbound

POPri: Private Federated Learning using Preference-Optimized Synthetic Data cites this paper.

POPri: Private Federated Learning using Preference-Optimized Synthetic Data Federated Evaluation and Tuning for On-Device Personalization: System Design & Applications

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-16T11:09:46.609318Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 077cfb41-82ac-4768-a840-1b6eaf74834e · inbound

Toward Malicious Clients Detection in Federated Learning cites this paper.

Toward Malicious Clients Detection in Federated Learning Federated Evaluation and Tuning for On-Device Personalization: System Design & Applications

Reference 2021

Resolution: unresolved; no resolver link, observed 2026-08-15T21:46:31.393400Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 67ebfd2d-a456-48a7-8ded-da6b3606f712 · inbound

What Makes Local Updates Effective: The Role of Data Heterogeneity and Smoothness cites this paper.

What Makes Local Updates Effective: The Role of Data Heterogeneity and Smoothness Federated Evaluation and Tuning for On-Device Personalization: System Design & Applications

Reference 119

Resolution: unresolved; no resolver link, observed 2026-08-06T21:27:28.147275Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 86a2ec3f-af2d-43dc-b69b-b91c3dcb0751 · inbound

On Hyperparameters and Backdoor-Resistance in Horizontal Federated Learning cites this paper.

On Hyperparameters and Backdoor-Resistance in Horizontal Federated Learning Federated Evaluation and Tuning for On-Device Personalization: System Design & Applications

Reference 43

Resolution: unresolved; no resolver link, observed 2026-08-05T05:35:20.693462Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fc598846-7b67-4501-8392-161963a074c3 · inbound

SecureAFL: Secure Asynchronous Federated Learning cites this paper.

SecureAFL: Secure Asynchronous Federated Learning Federated Evaluation and Tuning for On-Device Personalization: System Design & Applications

Reference 60

Resolution: metadata mismatch; arxiv_id, observed 2026-05-13T17:08:01.685977Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 4ea485ec-e8bb-4031-ad62-73ca33ed61b0 · inbound

Statistical Limits and Efficient Algorithms for Differentially Private Federated Learning cites this paper.

Statistical Limits and Efficient Algorithms for Differentially Private Federated Learning Federated Evaluation and Tuning for On-Device Personalization: System Design & Applications

Reference 9

Resolution: verified exact; arxiv_id, observed 2026-05-20T08:03:08.741708Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation e13e76e8-7321-4c19-994c-00110eb8331f · inbound

Totoro$^+$: An Adaptive and Scalable Edge Federated Learning System cites this paper.

Totoro$^+$: An Adaptive and Scalable Edge Federated Learning System Federated Evaluation and Tuning for On-Device Personalization: System Design & Applications

Reference 33

Resolution: verified exact; arxiv_id, observed 2026-07-01T16:45:51.874559Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation b7b6bd45-8a51-41bd-ba15-c3037b6717aa · inbound

Personalized Federated Learning via Variance-Aware Nonparametric Empirical Bayes cites this paper.

Personalized Federated Learning via Variance-Aware Nonparametric Empirical Bayes Federated Evaluation and Tuning for On-Device Personalization: System Design & Applications

Reference 81

Resolution: unresolved; no resolver link, observed 2026-08-12T00:13:13.692718Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.