Paper Citation Record · LEDGER

Improving Federated Learning Personalization via Model Agnostic Meta Learning

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 11 inbound Pith citation observations for arXiv:1909.12488.

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

pith.paper-citation-record.v1
1909.12488 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 11 of 11 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 11 of 11 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T15:21:58.256225Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-07-10T13:47:05.777666Z

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 98aeb881-7d5e-4f06-b20d-457830ee2f85 · inbound

An Image is Worth One Word: Personalizing Text-to-Image Generation using Textual Inversion cites this paper.

An Image is Worth One Word: Personalizing Text-to-Image Generation using Textual Inversion Improving Federated Learning Personalization via Model Agnostic Meta Learning

Reference 12

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T18:08:55.555099Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 20bcf3ed-de00-458a-be58-dcc9321f1101 · inbound

Federated Learning with Unlabeled Clients: Personalization Can Happen in Low Dimensions cites this paper.

Federated Learning with Unlabeled Clients: Personalization Can Happen in Low Dimensions Improving Federated Learning Personalization via Model Agnostic Meta Learning

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-07T15:21:58.256225Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 533696a9-288b-49e3-bc85-c6696eefa77c · inbound

Addressing the Collaboration Dilemma in Low-Data Federated Learning via Transient Sparsity cites this paper.

Addressing the Collaboration Dilemma in Low-Data Federated Learning via Transient Sparsity Improving Federated Learning Personalization via Model Agnostic Meta Learning

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-07T12:01:27.817834Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4dd77d4a-d311-46c8-8674-1cb5ff0a0401 · inbound

The OCR Quest for Generalization: Learning to recognize low-resource alphabets with model editing cites this paper.

The OCR Quest for Generalization: Learning to recognize low-resource alphabets with model editing Improving Federated Learning Personalization via Model Agnostic Meta Learning

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-07T05:56:46.976358Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 22a99a24-a87f-4580-b194-123d52feb0a0 · inbound

FedMeNF: Privacy-Preserving Federated Meta-Learning for Neural Fields cites this paper.

FedMeNF: Privacy-Preserving Federated Meta-Learning for Neural Fields Improving Federated Learning Personalization via Model Agnostic Meta Learning

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-05T22:57:20.389192Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation dc972a1b-c860-4ee1-a5b3-4b4ccb0ca33b · inbound

Federated Learning with Heterogeneous and Private Label Sets cites this paper.

Federated Learning with Heterogeneous and Private Label Sets Improving Federated Learning Personalization via Model Agnostic Meta Learning

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-05T16:18:10.039966Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 295fa256-1414-4a00-8835-8d4666815814 · inbound

SuperSFL: Resource-Heterogeneous Federated Split Learning with Weight-Sharing Super-Networks cites this paper.

SuperSFL: Resource-Heterogeneous Federated Split Learning with Weight-Sharing Super-Networks Improving Federated Learning Personalization via Model Agnostic Meta Learning

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-03T12:42:41.190170Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation af047e75-8419-415a-ba86-cfe78e1c25fc · inbound

Representation-Aligned Multi-Scale Personalization for Federated Learning cites this paper.

Representation-Aligned Multi-Scale Personalization for Federated Learning Improving Federated Learning Personalization via Model Agnostic Meta Learning

Reference 9

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T09:56:01.447714Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation e2456121-c503-48e8-8b82-069c898c26ce · inbound

Collaborative Yet Personalized Policy Training: Single-Timescale Federated Actor-Critic cites this paper.

Collaborative Yet Personalized Policy Training: Single-Timescale Federated Actor-Critic Improving Federated Learning Personalization via Model Agnostic Meta Learning

Reference 16

Resolution: verified exact; arxiv_id, observed 2026-05-15T02:08:29.357060Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 5d60feca-af81-4790-a5c0-f43d97129907 · inbound

Range Penalization: Theoretical Insights with Applications in Federated Learning cites this paper.

Range Penalization: Theoretical Insights with Applications in Federated Learning Improving Federated Learning Personalization via Model Agnostic Meta Learning

Reference 62

Resolution: metadata mismatch; arxiv_id, observed 2026-07-03T07:57:44.672827Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation cc1c2751-9614-4a78-88df-cff1151488ef · inbound

Collate: Collaborative Neural Network Learning for Latency-Critical Edge Systems cites this paper.

Collate: Collaborative Neural Network Learning for Latency-Critical Edge Systems Improving Federated Learning Personalization via Model Agnostic Meta Learning

Reference 17

Resolution: metadata mismatch; local_arxiv, observed 2026-07-10T13:47:05.778925Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.