Paper Citation Record · LEDGER

Federated Learning Based on Dynamic Regularization

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 31 inbound Pith citation observations for arXiv:2111.04263.

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

pith.paper-citation-record.v1
2111.04263 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 31 of 31 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 31 of 31 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-08T13:56:54.001172Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T21:58:58.236056Z

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 85c69d0e-624c-4efc-ae3a-b816ae03ccb1 · inbound

Federated Continual Learning: Concepts, Challenges, and Solutions cites this paper.

Federated Continual Learning: Concepts, Challenges, and Solutions Federated Learning Based on Dynamic Regularization

Reference 172

Resolution: unresolved; no resolver link, observed 2026-08-08T13:56:54.001172Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9783d785-78d5-474f-9b27-d1ad534d8390 · inbound

Distributionally Robust Federated Learning with Client Drift Minimization cites this paper.

Distributionally Robust Federated Learning with Client Drift Minimization Federated Learning Based on Dynamic Regularization

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-07T15:25:38.577958Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cac5a2d5-0cf6-4f7c-9634-0c96c30bb052 · inbound

Avoid Forgetting by Preserving Global Knowledge Gradients in Federated Learning with Non-IID Data cites this paper.

Avoid Forgetting by Preserving Global Knowledge Gradients in Federated Learning with Non-IID Data Federated Learning Based on Dynamic Regularization

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-07T13:59:33.793400Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 00cecdae-f551-40ae-8cdf-3b9078a46ba6 · inbound

Label-shift robust federated feature screening for high-dimensional classification cites this paper.

Label-shift robust federated feature screening for high-dimensional classification Federated Learning Based on Dynamic Regularization

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-07T12:13:49.790586Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bf85a2fc-968e-48dc-aa60-63b7a38d3d07 · inbound

Towards Graph-Based Privacy-Preserving Federated Learning: ModelNet -- A ResNet-based Model Classification Dataset cites this paper.

Towards Graph-Based Privacy-Preserving Federated Learning: ModelNet -- A ResNet-based Model Classification Dataset Federated Learning Based on Dynamic Regularization

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-07T12:08:02.906703Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e0f3bf3d-0882-4b8c-a40d-bcd12b99ecdb · inbound

Mitigating Non-IID Drift in Zeroth-Order Federated LLM Fine-Tuning with Transferable Sparsity cites this paper.

Mitigating Non-IID Drift in Zeroth-Order Federated LLM Fine-Tuning with Transferable Sparsity Federated Learning Based on Dynamic Regularization

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-07T11:16:19.831388Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b6a85448-1fa7-4272-bd00-6744c36ec56f · inbound

UniVarFL: Uniformity and Variance Regularized Federated Learning for Heterogeneous Data cites this paper.

UniVarFL: Uniformity and Variance Regularized Federated Learning for Heterogeneous Data Federated Learning Based on Dynamic Regularization

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-07T05:22:27.159468Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8f3a80c1-e755-4a52-802c-2d2532da6506 · inbound

AFBS:Buffer Gradient Selection in Semi-asynchronous Federated Learning cites this paper.

AFBS:Buffer Gradient Selection in Semi-asynchronous Federated Learning Federated Learning Based on Dynamic Regularization

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-07T00:52:38.439341Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8687a53b-0a8c-4d4e-9855-33111f3979ab · inbound

Distilling A Universal Expert from Clustered Federated Learning cites this paper.

Distilling A Universal Expert from Clustered Federated Learning Federated Learning Based on Dynamic Regularization

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-06T22:59:13.711377Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7b541e1d-1ec0-4285-a6d8-c82ebf5db17b · inbound

FedWCM: Unleashing the Potential of Momentum-based Federated Learning in Long-Tailed Scenarios cites this paper.

FedWCM: Unleashing the Potential of Momentum-based Federated Learning in Long-Tailed Scenarios Federated Learning Based on Dynamic Regularization

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-06T15:49:03.246717Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fdea6aa1-2d31-4282-a87a-51600b442fbc · inbound

Multi-Hop Privacy Propagation for Differentially Private Federated Learning in Social Networks cites this paper.

Multi-Hop Privacy Propagation for Differentially Private Federated Learning in Social Networks Federated Learning Based on Dynamic Regularization

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-05T22:00:38.129774Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 92e11ab8-45aa-43e8-8e81-4d6d1f371385 · inbound

Generalizable Federated Learning using Client Adaptive Focal Modulation cites this paper.

Generalizable Federated Learning using Client Adaptive Focal Modulation Federated Learning Based on Dynamic Regularization

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-05T20:19:02.157280Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bc7cc74f-20ae-4e8b-bd87-3a24dbeccef6 · inbound

Degree of Staleness-Aware Data Updating in Federated Learning cites this paper.

Degree of Staleness-Aware Data Updating in Federated Learning Federated Learning Based on Dynamic Regularization

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-05T17:10:25.013084Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 981b63d9-dce4-4062-a089-c9ffa4a07ca2 · inbound

FedQuad: Federated Stochastic Quadruplet Learning to Mitigate Data Heterogeneity cites this paper.

FedQuad: Federated Stochastic Quadruplet Learning to Mitigate Data Heterogeneity Federated Learning Based on Dynamic Regularization

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-05T10:26:02.307748Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 666066c3-01f8-47d6-bfa0-2d28a8723a80 · inbound

Dissecting Federated-Graph Aggregation under Domain Shift: Importance-Aware Aggregation via Empirical Analysis cites this paper.

Dissecting Federated-Graph Aggregation under Domain Shift: Importance-Aware Aggregation via Empirical Analysis Federated Learning Based on Dynamic Regularization

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-04T16:33:59.844547Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bf9411b0-2bed-4d1f-adc8-ddf616b6ec42 · inbound

Adaptive Federated Learning to Optimize Integrated Flows in Cyber-Physical Data Centers cites this paper.

Adaptive Federated Learning to Optimize Integrated Flows in Cyber-Physical Data Centers Federated Learning Based on Dynamic Regularization

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-04T00:36:18.876710Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 84882b99-0c2c-4905-939b-d7335afdac25 · inbound

Rethinking the Personalized Relaxed Initialization in the Federated Learning: Consistency and Generalization cites this paper.

Rethinking the Personalized Relaxed Initialization in the Federated Learning: Consistency and Generalization Federated Learning Based on Dynamic Regularization

Reference 1

Resolution: verified exact; arxiv_id, observed 2026-05-11T09:00:59.574821Z

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 a734a6cb-a1f7-403d-ac43-8698f9ad9252 · inbound

Fed3D: Federated 3D Object Detection cites this paper.

Fed3D: Federated 3D Object Detection Federated Learning Based on Dynamic Regularization

Reference 23

Resolution: metadata mismatch; arxiv_id, observed 2026-05-10T08:22:37.071465Z

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 88c0810e-bee1-4755-b183-a5088032bf28 · inbound

Federated Distillation for Whole Slide Image via Gaussian-Mixture Feature Alignment and Curriculum Integration cites this paper.

Federated Distillation for Whole Slide Image via Gaussian-Mixture Feature Alignment and Curriculum Integration Federated Learning Based on Dynamic Regularization

Reference 68

Resolution: verified exact; arxiv_id, observed 2026-05-21T00:13:52.795479Z

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 1b44243f-8b5c-42f1-a0ad-98bc413747ce · inbound

FedFrozen: Two-Stage Federated Optimization via Attention Kernel Freezing cites this paper.

FedFrozen: Two-Stage Federated Optimization via Attention Kernel Freezing Federated Learning Based on Dynamic Regularization

Reference 1

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T19:01:19.593967Z

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 5b7cf47c-df04-4b68-8b84-a2570942474b · inbound

Enhancing Federated Quadruplet Learning: Stochastic Client Selection and Embedding Stability Analysis cites this paper.

Enhancing Federated Quadruplet Learning: Stochastic Client Selection and Embedding Stability Analysis Federated Learning Based on Dynamic Regularization

Reference 27

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T03:40:53.898205Z

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 9c5a1d01-eb76-4c7e-a7d3-58906b654c83 · inbound

Towards the Next Frontier of LLMs, Training on Private Data: A Cross-Domain Benchmark for Federated Fine-Tuning cites this paper.

Towards the Next Frontier of LLMs, Training on Private Data: A Cross-Domain Benchmark for Federated Fine-Tuning Federated Learning Based on Dynamic Regularization

Reference 26

Resolution: verified exact; arxiv_id, observed 2026-05-15T04:59:45.867165Z

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 d09b97bb-419e-44b6-ac0f-697316e94bec · inbound

BESplit: Bias-Compensated Split Federated Learning with Evidential Aggregation cites this paper.

BESplit: Bias-Compensated Split Federated Learning with Evidential Aggregation Federated Learning Based on Dynamic Regularization

Reference 22

Resolution: verified exact; arxiv_id, observed 2026-05-20T14:28:21.182271Z

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 a2a5db49-fba2-47e6-ae12-2aeb61f51cff · inbound

Benchmarking Federated Learning and Knowledge Distillation for Point Cloud Classification cites this paper.

Benchmarking Federated Learning and Knowledge Distillation for Point Cloud Classification Federated Learning Based on Dynamic Regularization

Reference 1

Resolution: verified exact; arxiv_id, observed 2026-07-03T21:58:58.238019Z

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 2e6888b8-93f2-49f6-8e9d-0a3c5bc2d149 · inbound

FedACT: Federated Adaptive Coordinate Trust Modulation for Robust Transformer Training under Data Heterogeneity cites this paper.

FedACT: Federated Adaptive Coordinate Trust Modulation for Robust Transformer Training under Data Heterogeneity Federated Learning Based on Dynamic Regularization

Reference 91

Resolution: unresolved; no resolver link, observed 2026-07-12T00:07:55.485589Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 199996e5-2815-4b50-a96e-58046336491c · inbound

HERO: A Heterogeneity-Aware Benchmark Library for Federated Continual Learning cites this paper.

HERO: A Heterogeneity-Aware Benchmark Library for Federated Continual Learning Federated Learning Based on Dynamic Regularization

Reference 51

Resolution: unresolved; no resolver link, observed 2026-07-13T07:32:39.495351Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f78c08c5-4c3b-4fd7-a993-a42154dbcffc · inbound

FM$^2$: Unified Federated Foundation Models for Heterogeneous Multimodal Medical Imaging cites this paper.

FM$^2$: Unified Federated Foundation Models for Heterogeneous Multimodal Medical Imaging Federated Learning Based on Dynamic Regularization

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-02T05:28:37.747662Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 02f3892d-0ad5-44ff-b98b-5c84160d6ebd · inbound

One Round Is All You Need: Analytic Federated Learning for Task-Heterogeneous Multi-Label Medical Image Classification cites this paper.

One Round Is All You Need: Analytic Federated Learning for Task-Heterogeneous Multi-Label Medical Image Classification Federated Learning Based on Dynamic Regularization

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-01T09:51:15.534889Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c08ff1dd-e206-4507-9347-70d44ea65b07 · inbound

TriShield: Zero-Utility-Loss Defense Against Privacy Backdoors in Federated Language Model Fine-Tuning via Orthogonal Gradient Projection and Optimizer State Entanglement cites this paper.

TriShield: Zero-Utility-Loss Defense Against Privacy Backdoors in Federated Language Model Fine-Tuning via Orthogonal Gradient Projection and Optimizer State Entanglement Federated Learning Based on Dynamic Regularization

Reference 16

Resolution: unresolved; no resolver link, observed 2026-07-31T22:47:13.870770Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation afee60e4-ce7c-48ad-9e71-0ea6e75cd5ed · inbound

TriShield: Zero-Utility-Loss Defense Against Privacy Backdoors in Federated Language Model Fine-Tuning via Orthogonal Gradient Projection and Optimizer State Entanglement cites this paper.

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-03T01:42:10.423582Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 06934989-31db-49c2-a423-11d5495153d9 · inbound

AS-FedBridge: Pseudo-Spike Bridge Distillation for Heterogeneous ANN-SNN Federated Learning cites this paper.

AS-FedBridge: Pseudo-Spike Bridge Distillation for Heterogeneous ANN-SNN Federated Learning Federated Learning Based on Dynamic Regularization

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-05T21:03:54.443436Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.