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Paper Citation Record · LEDGER

Gradient Correction in Federated Learning with Adaptive Optimization

As of 9 August 2026, this Paper Citation Record lists 36 of 36 outbound references and 2 inbound Pith citation observations for arXiv:2502.02727.

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

pith.paper-citation-record.v1
2502.02727 v3

Coverage vector

measured 36 of 36 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-09T11:30:47.029675Z

measured 38 of 38 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 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-07-12T00:07:55.485589Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-11T10:51:22.663894Z

Reference resolution

36 of 36 outbound references displayed

  • verified exact5
  • verified fuzzy20
  • unresolved11
  • parse uncertain0
  • malformed identifier0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 4c8a155e-e227-4d77-8a6b-143501608ee4 · outbound

This paper cites Federated learning: Challenges, methods, and future directions,.

Gradient Correction in Federated Learning with Adaptive Optimization Federated learning: Challenges, methods, and future directions,

Reference 1

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Unavailable: canonical work link unavailable.

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Observation 6c048ee6-7bba-4147-8035-89c45390ab5b · outbound

This paper cites Advances and open problems in federated learning,.

Gradient Correction in Federated Learning with Adaptive Optimization Advances and open problems in federated learning,

Reference 2

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Source-reported events for the cited work

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Observation d82de800-d688-479a-aa6e-9a3d9cb1972c · outbound

This paper cites Adaptive subgradient methods for online learning and stochastic optimization.

Gradient Correction in Federated Learning with Adaptive Optimization Adaptive subgradient methods for online learning and stochastic optimization

Reference 3

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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.

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Observation 8443b6fc-0f01-4f8e-8a18-792172bb17dd · outbound

This paper cites Generating Sequences With Recurrent Neural Networks.

Gradient Correction in Federated Learning with Adaptive Optimization Generating Sequences With Recurrent Neural Networks

Reference 4

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no resolver link, observed 2026-08-09T11:30:46.914406Z

Source-reported events for the cited work

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Observation 725167c7-cba0-4d5b-a253-6e6fbbd8e425 · outbound

This paper cites Adam: A Method for Stochastic Optimization.

Gradient Correction in Federated Learning with Adaptive Optimization Adam: A Method for Stochastic Optimization

Reference 5

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Observation 5037be44-78d3-4be4-af5f-0f9666cfccd5 · outbound

This paper cites Towards building the federatedgpt: Federated instruction tuning,.

Gradient Correction in Federated Learning with Adaptive Optimization Towards building the federatedgpt: Federated instruction tuning,

Reference 6

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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.

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Observation fb649365-9285-45a0-bb78-5a07f0ef98de · outbound

This paper cites Momentum Benefits Non-IID Federated Learning Simply and Provably.

Gradient Correction in Federated Learning with Adaptive Optimization Momentum Benefits Non-IID Federated Learning Simply and Provably

Reference 7

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation a3c1fbdd-90a9-4cb0-b48f-c454583af325 · outbound

This paper cites Adaptive Federated Optimization.

Gradient Correction in Federated Learning with Adaptive Optimization Adaptive Federated Optimization

Reference 8

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Observation 74c7907b-02c5-45fd-ba16-e901bbf78b2b · outbound

This paper cites Communication-efficient adaptive federated learning,.

Gradient Correction in Federated Learning with Adaptive Optimization Communication-efficient adaptive federated learning,

Reference 9

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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.

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Observation 682a21c9-d4ac-41e5-88e0-ab184795f3fa · outbound

This paper cites Scaffold: Stochastic controlled averaging for federated learning,.

Gradient Correction in Federated Learning with Adaptive Optimization Scaffold: Stochastic controlled averaging for federated learning,

Reference 10

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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.

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Observation d2423329-a093-4690-bbc9-b80b6d83c61a · outbound

This paper cites Proxskip: Yes! local gradient steps provably lead to communication acceleration! finally!.

Gradient Correction in Federated Learning with Adaptive Optimization Proxskip: Yes! local gradient steps provably lead to communication acceleration! finally!

Reference 11

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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.

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Observation 69e76932-930f-46f1-8564-0680fe7da0eb · outbound

This paper cites Next: In-network nonconvex optimization,.

Gradient Correction in Federated Learning with Adaptive Optimization Next: In-network nonconvex optimization,

Reference 12

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 5ed85afe-82c2-40f7-88f9-f616b75a54a3 · outbound

This paper cites Achieving geometric convergence for distributed optimization over time-varying graphs,.

Gradient Correction in Federated Learning with Adaptive Optimization Achieving geometric convergence for distributed optimization over time-varying graphs,

Reference 13

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Source-reported events for the cited work

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Observation 95695845-0e8b-4626-9075-923114e3b276 · outbound

This paper cites Asy-sonata: Achieving linear convergence in distributed asynchronous multiagent optimization,.

Gradient Correction in Federated Learning with Adaptive Optimization Asy-sonata: Achieving linear convergence in distributed asynchronous multiagent optimization,

Reference 14

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verified fuzzy
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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.

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Observation 9fb96d92-2abc-456b-b6e6-4336c6a476e0 · outbound

This paper cites An improved analysis of gradient tracking for decentralized machine learning,.

Gradient Correction in Federated Learning with Adaptive Optimization An improved analysis of gradient tracking for decentralized machine learning,

Reference 15

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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.

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Observation 906d4d50-6f7e-4526-842e-6dd91daea907 · outbound

This paper cites Gtadam: Gradient tracking with adaptive momentum for distributed online optimization,.

Gradient Correction in Federated Learning with Adaptive Optimization Gtadam: Gradient tracking with adaptive momentum for distributed online optimization,

Reference 16

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verified fuzzy
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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.

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Observation 1a7b79cb-6b83-4f9e-8bca-d2d6f86833e1 · outbound

This paper cites Momentum Tracking: Momentum Acceleration for Decentralized Deep Learning on Heterogeneous Data.

Gradient Correction in Federated Learning with Adaptive Optimization Momentum Tracking: Momentum Acceleration for Decentralized Deep Learning on Heterogeneous Data

Reference 17

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verified exact
local_arxiv, observed 2026-08-09T11:30:47.154659Z

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.

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Observation 57c66aa1-084d-407a-8b6d-ee1f93ec0dcd · outbound

This paper cites Momentum-based distributed gradient tracking algorithms for distributed aggregative optimization over unbalanced directed graphs,.

Gradient Correction in Federated Learning with Adaptive Optimization Momentum-based distributed gradient tracking algorithms for distributed aggregative optimization over unbalanced directed graphs,

Reference 18

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raw_fallback, observed 2026-08-09T11:30:47.608918Z

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.

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Observation a9a98f34-37e3-4d97-854d-b88e19d975c1 · outbound

This paper cites Towards optimal communication complexity in distributed non-convex optimization,.

Gradient Correction in Federated Learning with Adaptive Optimization Towards optimal communication complexity in distributed non-convex optimization,

Reference 19

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verified fuzzy
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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.

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Observation 51afbb62-e875-47cd-839b-2b46fda3ee8e · outbound

This paper cites Decentralized Gradient Tracking with Local Steps.

Gradient Correction in Federated Learning with Adaptive Optimization Decentralized Gradient Tracking with Local Steps

Reference 20

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verified exact
local_arxiv, observed 2026-08-09T11:30:47.140518Z

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.

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Observation 2af15478-6794-4df5-8524-787c48a77282 · outbound

This paper cites Gradient and Variable Tracking with Multiple Local SGD for Decentralized Non-Convex Learning.

Gradient Correction in Federated Learning with Adaptive Optimization Gradient and Variable Tracking with Multiple Local SGD for Decentralized Non-Convex Learning

Reference 21

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verified exact
local_arxiv, observed 2026-08-09T11:30:47.127336Z

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.

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Observation e25e76b3-55f0-45bf-8ab1-a815db76f3b8 · outbound

This paper cites Balancing Communication and Computation in Gradient Tracking Algorithms for Decentralized Optimization.

Gradient Correction in Federated Learning with Adaptive Optimization Balancing Communication and Computation in Gradient Tracking Algorithms for Decentralized Optimization

Reference 22

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verified exact
local_arxiv, observed 2026-08-09T11:30:47.113270Z

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.

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Observation d8f6e3ce-487e-450a-959e-244315ea8dae · outbound

This paper cites Local exact-diffusion for decentralized optimization and learning,.

Gradient Correction in Federated Learning with Adaptive Optimization Local exact-diffusion for decentralized optimization and learning,

Reference 23

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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.

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Observation 5900930e-92ab-4d82-8f72-1670a0ede5d7 · outbound

This paper cites Taming subnet-drift in d2d-enabled fog learning: A hierarchicalgradienttrackingapproach,.

Gradient Correction in Federated Learning with Adaptive Optimization Taming subnet-drift in d2d-enabled fog learning: A hierarchicalgradienttrackingapproach,

Reference 24

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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.

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Observation e5545712-4f78-49ee-ac18-f9dc29ee2285 · outbound

This paper cites Hierarchical federated learning with multi-timescale gradient correction,.

Gradient Correction in Federated Learning with Adaptive Optimization Hierarchical federated learning with multi-timescale gradient correction,

Reference 25

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verified fuzzy
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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.

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Observation 14f04332-0425-433e-b36b-d5067586ae2e · outbound

This paper cites Decoupled Weight Decay Regularization.

Gradient Correction in Federated Learning with Adaptive Optimization Decoupled Weight Decay Regularization

Reference 26

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 0f45ad9a-74b4-4d26-852f-9ce372673d16 · outbound

This paper cites On the overlooked pitfalls of weight decay and how to mitigate them: A gradient-norm perspective,.

Gradient Correction in Federated Learning with Adaptive Optimization On the overlooked pitfalls of weight decay and how to mitigate them: A gradient-norm perspective,

Reference 27

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verified fuzzy
raw_fallback, observed 2026-08-09T11:30:47.376116Z

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.

source=pdf_text observed=2026-08-09T11:30:46.996148Z digest=sha256:a592f6cfb746787b5271d11a450d2fd993c3b4e63b750022e78d40f289edc4de

Observation e4f397d0-9a74-49d4-9382-e4cb94b5c768 · outbound

This paper cites Local AdaAlter: Communication-Efficient Stochastic Gradient Descent with Adaptive Learning Rates.

Gradient Correction in Federated Learning with Adaptive Optimization Local AdaAlter: Communication-Efficient Stochastic Gradient Descent with Adaptive Learning Rates

Reference 28

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no resolver link, observed 2026-08-09T11:30:47.000250Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T11:30:47.000250Z digest=sha256:b8e8bcb3e7eaaf25b0f2a6ff367803a80a29a2c31e317d5da95a1258edbfd3d5

Observation 59fe363b-9fac-445a-903e-6a2625c9f48e · outbound

This paper cites Efficient Federated Learning via Local Adaptive Amended Optimizer with Linear Speedup.

Gradient Correction in Federated Learning with Adaptive Optimization Efficient Federated Learning via Local Adaptive Amended Optimizer with Linear Speedup

Reference 29

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verified exact
local_arxiv, observed 2026-08-09T11:30:47.078482Z

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.

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Observation fbf36c00-be84-4aed-b13a-747cbaaa51b4 · outbound

This paper cites A sufficient condition for convergences of adam and rmsprop,.

Gradient Correction in Federated Learning with Adaptive Optimization A sufficient condition for convergences of adam and rmsprop,

Reference 30

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verified fuzzy
raw_fallback, observed 2026-08-09T11:30:47.355185Z

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.

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Observation 0befee3f-02f5-4ebd-9c82-60f7a9b59120 · outbound

This paper cites Learning multiple layers of features from tiny images,.

Gradient Correction in Federated Learning with Adaptive Optimization Learning multiple layers of features from tiny images,

Reference 31

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verified fuzzy
raw_fallback, observed 2026-08-09T11:30:47.345272Z

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.

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Observation 76eb9631-134c-4442-8747-b2cb69579ac5 · outbound

This paper cites Tiny imagenet visual recognition challenge,.

Gradient Correction in Federated Learning with Adaptive Optimization Tiny imagenet visual recognition challenge,

Reference 32

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unresolved
no resolver link, observed 2026-08-09T11:30:47.014982Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation b2aa42e8-c509-4e75-ad37-707142b2dd54 · outbound

This paper cites Lora: Low-rank adaptation of large language models.

Gradient Correction in Federated Learning with Adaptive Optimization Lora: Low-rank adaptation of large language models

Reference 33

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raw_fallback, observed 2026-08-09T11:30:47.302456Z

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.

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Observation 1023862d-efcd-4ae9-a297-97bf429e09d8 · outbound

This paper cites Language models are unsupervised multitask learners,.

Gradient Correction in Federated Learning with Adaptive Optimization Language models are unsupervised multitask learners,

Reference 34

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raw_fallback, observed 2026-08-09T11:30:47.257458Z

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.

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Observation 799a9b87-ff15-4a8b-814f-647653a3de0a · outbound

This paper cites Newsweeder: Learning to filter netnews,.

Gradient Correction in Federated Learning with Adaptive Optimization Newsweeder: Learning to filter netnews,

Reference 35

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raw_fallback, observed 2026-08-09T11:30:47.215877Z

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.

source=pdf_text observed=2026-08-09T11:30:47.025501Z digest=sha256:a4a4f9fd606b9abbb833f1d6ed5a20f7db2c02f8d506d53c2b1c920bb4133273

Observation 87564f78-904d-4caa-8b7e-18fadf24f796 · outbound

This paper cites GLUE: A Multi-Task Benchmark and Analysis Platform for Natural Language Understanding.

Gradient Correction in Federated Learning with Adaptive Optimization GLUE: A Multi-Task Benchmark and Analysis Platform for Natural Language Understanding

Reference 36

Resolution
unresolved
no resolver link, observed 2026-08-09T11:30:47.029675Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T11:30:47.029675Z digest=sha256:454d087df6fa0ba6b6819f3ead9dce1438742815c89d1f6b9673709174ad1691

Pith citing papers

Observation 6680cba9-cb6c-47b6-937a-807eeff0f985 · inbound

Evolution of Optimization Methods: Algorithms, Scenarios, and Evaluations cites this paper.

Evolution of Optimization Methods: Algorithms, Scenarios, and Evaluations Gradient Correction in Federated Learning with Adaptive Optimization

Reference 4

Resolution
verified exact
arxiv_id, observed 2026-05-11T10:51:22.707348Z

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.

source=pdf_text observed=2026-05-10T15:16:58.221358Z digest=sha256:7713ecc3d5ccd43f973bb2793905cd2c4d1f8003dd3f7d7caef023f10326df8b

Observation 73cc9b2e-4a30-44c4-9445-dcd0b8f43a45 · 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 Gradient Correction in Federated Learning with Adaptive Optimization

Reference 70

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-12T00:07:55.485589Z digest=sha256:bbdb11bf179d5f161e5714e9a1a681d9398164836bf50a6edfa38e74ba955e02