Paper Citation Record · LEDGER

Federated Deconfounding and Debiasing Learning for Out-of-Distribution Generalization

As of 17 August 2026, this Paper Citation Record lists 53 of 53 outbound references and 2 inbound Pith citation observations for arXiv:2505.04979.

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

pith.paper-citation-record.v1
2505.04979 v2

Coverage vector

measured 53 of 53 reference resolution

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measured 55 of 55 standing notices

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measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-14T04:37:52.592019Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-14T04:37:52.672561Z

Reference resolution

53 of 53 outbound references displayed

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External citation measurements

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Outbound references

Observation bab3d17c-bcd4-4a7f-98f3-e5c0882fa228 · outbound

This paper cites Mitigating Data Heterogeneity in Federated Learning with Data Augmentation.

Federated Deconfounding and Debiasing Learning for Out-of-Distribution Generalization Mitigating Data Heterogeneity in Federated Learning with Data Augmentation

Reference 3

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Observation bf0073b6-3420-4e0e-8fec-8aa3cfc33058 · outbound

This paper cites Deep residual learning for image recog- nition.

Federated Deconfounding and Debiasing Learning for Out-of-Distribution Generalization Deep residual learning for image recog- nition

Reference 6

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Observation 0d17ba5d-a661-446d-991e-c84442f73834 · outbound

This paper cites Fedmut: Generalized federated learning via stochastic mu- tation.

Federated Deconfounding and Debiasing Learning for Out-of-Distribution Generalization Fedmut: Generalized federated learning via stochastic mu- tation

Reference 8

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This paper cites Re- thinking federated learning with domain shift: A prototype view.

Federated Deconfounding and Debiasing Learning for Out-of-Distribution Generalization Re- thinking federated learning with domain shift: A prototype view

Reference 9

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Observation 6cbabdbf-bf26-494f-acc7-0939745defc0 · outbound

This paper cites A cross-client coordinator in fed- erated learning framework for conquering heterogeneity.

Federated Deconfounding and Debiasing Learning for Out-of-Distribution Generalization A cross-client coordinator in fed- erated learning framework for conquering heterogeneity

Reference 10

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Observation bd6eb446-70a8-4875-8744-135feebe787e · outbound

This paper cites Feder- ated optimization in heterogeneous networks.Proceedings of Machine learning and systems, 2:429–450,.

Federated Deconfounding and Debiasing Learning for Out-of-Distribution Generalization Feder- ated optimization in heterogeneous networks.Proceedings of Machine learning and systems, 2:429–450,

Reference 11

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Observation 07501538-fb40-4001-8ead-4266669fb13a · outbound

This paper cites Multi-source domain adaptation for visual sentiment classification.

Federated Deconfounding and Debiasing Learning for Out-of-Distribution Generalization Multi-source domain adaptation for visual sentiment classification

Reference 14

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Observation 805228a1-26b1-4d68-8afa-b6311f044afb · outbound

This paper cites Grounding dino: Marrying dino with grounded pre-training for open-set ob- ject detection.

Federated Deconfounding and Debiasing Learning for Out-of-Distribution Generalization Grounding dino: Marrying dino with grounded pre-training for open-set ob- ject detection

Reference 15

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This paper cites Feddg: Federated domain generalization on medi- cal image segmentation via episodic learning in continu- ous frequency space.

Federated Deconfounding and Debiasing Learning for Out-of-Distribution Generalization Feddg: Federated domain generalization on medi- cal image segmentation via episodic learning in continu- ous frequency space

Reference 16

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Observation e5d19846-bf7f-4d75-a49f-810b5d2a06d4 · outbound

This paper cites Disentangled Federated Learning for Tackling Attributes Skew via Invariant Aggregation and Diversity Transferring.

Federated Deconfounding and Debiasing Learning for Out-of-Distribution Generalization Disentangled Federated Learning for Tackling Attributes Skew via Invariant Aggregation and Diversity Transferring

Reference 17

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Observation 07192586-721c-4d51-84b5-6fa3514dcb6d · outbound

This paper cites Communication-efficient learn- ing of deep networks from decentralized data.

Federated Deconfounding and Debiasing Learning for Out-of-Distribution Generalization Communication-efficient learn- ing of deep networks from decentralized data

Reference 18

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Observation 640c6082-f45b-43af-84a8-a03be585a3c3 · outbound

This paper cites Stable Diffusion-based Data Augmentation for Federated Learning with Non-IID Data.

Federated Deconfounding and Debiasing Learning for Out-of-Distribution Generalization Stable Diffusion-based Data Augmentation for Federated Learning with Non-IID Data

Reference 21

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This paper cites Fedproc: Prototypical contrastive federated learning on non-iid data.

Federated Deconfounding and Debiasing Learning for Out-of-Distribution Generalization Fedproc: Prototypical contrastive federated learning on non-iid data

Reference 22

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Observation 49b1315f-3ca6-419e-adbf-07c79b343c52 · outbound

This paper cites PARDON: Privacy-Aware and Robust Federated Domain Generalization.

Federated Deconfounding and Debiasing Learning for Out-of-Distribution Generalization PARDON: Privacy-Aware and Robust Federated Domain Generalization

Reference 23

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Observation 4f7f626d-0d95-4ee3-934d-a1c73292d7fe · outbound

This paper cites Stablefdg: style and attention based learning for federated domain generalization.

Federated Deconfounding and Debiasing Learning for Out-of-Distribution Generalization Stablefdg: style and attention based learning for federated domain generalization

Reference 24

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Observation 00822fa1-570b-47d4-9d9a-fbf36bddcddf · outbound

This paper cites Attentive model- ing and distillation for out-of-distribution generalization of federated learning.

Federated Deconfounding and Debiasing Learning for Out-of-Distribution Generalization Attentive model- ing and distillation for out-of-distribution generalization of federated learning

Reference 25

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Observation edfd9b87-08aa-4f9d-89bc-ab1c22b5fbba · outbound

This paper cites Clustering-based curriculum construction for sample-balanced federated learning.

Federated Deconfounding and Debiasing Learning for Out-of-Distribution Generalization Clustering-based curriculum construction for sample-balanced federated learning

Reference 26

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This paper cites Cross-silo prototypical calibration for federated learning with non-iid data.

Federated Deconfounding and Debiasing Learning for Out-of-Distribution Generalization Cross-silo prototypical calibration for federated learning with non-iid data

Reference 27

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This paper cites Cross-training with multi-view knowl- edge fusion for heterogenous federated learning.

Federated Deconfounding and Debiasing Learning for Out-of-Distribution Generalization Cross-training with multi-view knowl- edge fusion for heterogenous federated learning

Reference 28

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This paper cites Advances and open chal- lenges in federated foundation models.

Federated Deconfounding and Debiasing Learning for Out-of-Distribution Generalization Advances and open chal- lenges in federated foundation models

Reference 29

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Observation 88b0ddde-cb6e-443f-bd00-fd0df62e21a9 · outbound

This paper cites Grad-cam: Visual explanations from deep networks via gradient-based local- ization.

Federated Deconfounding and Debiasing Learning for Out-of-Distribution Generalization Grad-cam: Visual explanations from deep networks via gradient-based local- ization

Reference 30

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This paper cites Learning across domains and devices: Style-driven source-free domain adaptation in clustered federated learning.

Federated Deconfounding and Debiasing Learning for Out-of-Distribution Generalization Learning across domains and devices: Style-driven source-free domain adaptation in clustered federated learning

Reference 31

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This paper cites Understanding and mitigating di- mensional collapse in federated learning.

Federated Deconfounding and Debiasing Learning for Out-of-Distribution Generalization Understanding and mitigating di- mensional collapse in federated learning

Reference 32

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This paper cites Cxr-fl: deep learning-based chest x-ray image analysis using federated learning.

Federated Deconfounding and Debiasing Learning for Out-of-Distribution Generalization Cxr-fl: deep learning-based chest x-ray image analysis using federated learning

Reference 33

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This paper cites Feature distribution matching for federated domain gener- alization.

Federated Deconfounding and Debiasing Learning for Out-of-Distribution Generalization Feature distribution matching for federated domain gener- alization

Reference 34

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Observation 6a2d110f-069b-4760-b294-f5e15e8d15c1 · outbound

This paper cites Visualizing data using t-sne.

Federated Deconfounding and Debiasing Learning for Out-of-Distribution Generalization Visualizing data using t-sne

Reference 35

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Observation 9cfbced9-b0cf-42bd-bbe2-7f392539c56c · outbound

This paper cites Causal attention for unbiased visual recognition.

Federated Deconfounding and Debiasing Learning for Out-of-Distribution Generalization Causal attention for unbiased visual recognition

Reference 37

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This paper cites Meta-causal feature learning for out-of-distribution gener- alization.

Federated Deconfounding and Debiasing Learning for Out-of-Distribution Generalization Meta-causal feature learning for out-of-distribution gener- alization

Reference 38

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This paper cites Dafkd: Domain-aware federated knowledge distillation.

Federated Deconfounding and Debiasing Learning for Out-of-Distribution Generalization Dafkd: Domain-aware federated knowledge distillation

Reference 39

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This paper cites Fedcda: Federated learning with cross-rounds divergence-aware aggregation.

Federated Deconfounding and Debiasing Learning for Out-of-Distribution Generalization Fedcda: Federated learning with cross-rounds divergence-aware aggregation

Reference 40

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Observation 8908d5f4-5e81-4fb9-84a8-2ebe9a0c7593 · outbound

This paper cites Multi- source collaborative gradient discrepancy minimization for federated domain generalization.

Federated Deconfounding and Debiasing Learning for Out-of-Distribution Generalization Multi- source collaborative gradient discrepancy minimization for federated domain generalization

Reference 41

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This paper cites Federated adversarial domain halluci- nation for privacy-preserving domain generalization.IEEE Transactions on Multimedia, 26:1–14,.

Federated Deconfounding and Debiasing Learning for Out-of-Distribution Generalization Federated adversarial domain halluci- nation for privacy-preserving domain generalization.IEEE Transactions on Multimedia, 26:1–14,

Reference 42

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This paper cites Fed- erated learning: Privacy and incentive,.

Federated Deconfounding and Debiasing Learning for Out-of-Distribution Generalization Fed- erated learning: Privacy and incentive,

Reference 43

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This paper cites Fedgh: Heterogeneous federated learning with generalized global header.

Federated Deconfounding and Debiasing Learning for Out-of-Distribution Generalization Fedgh: Heterogeneous federated learning with generalized global header

Reference 44

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This paper cites Fed- erated model heterogeneous matryoshka representation learning.

Federated Deconfounding and Debiasing Learning for Out-of-Distribution Generalization Fed- erated model heterogeneous matryoshka representation learning

Reference 45

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Observation 66f4c0b4-8b4c-46d5-9d89-c664040e2e6b · outbound

This paper cites Dynamic witness se- lection for trustworthy distributed cooperative sensing in cognitive radio networks.

Federated Deconfounding and Debiasing Learning for Out-of-Distribution Generalization Dynamic witness se- lection for trustworthy distributed cooperative sensing in cognitive radio networks

Reference 46

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Observation 62026052-81a6-4f23-8570-dd96786cc32a · outbound

This paper cites Enabling collaborative test-time adaptation in dynamic environment via federated learning.

Federated Deconfounding and Debiasing Learning for Out-of-Distribution Generalization Enabling collaborative test-time adaptation in dynamic environment via federated learning

Reference 48

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Observation f76286af-f03d-4156-8d7d-2e3800b58293 · outbound

This paper cites Federated analytics with data augmentation in domain generalization towards future networks.

Federated Deconfounding and Debiasing Learning for Out-of-Distribution Generalization Federated analytics with data augmentation in domain generalization towards future networks

Reference 49

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Observation 7ad91f5b-7f85-4426-9cd4-ad9174c05e5e · outbound

This paper cites Federated Out-of-Distribution Generalization: A Causal Augmentation View.

Federated Deconfounding and Debiasing Learning for Out-of-Distribution Generalization Federated Out-of-Distribution Generalization: A Causal Augmentation View

Reference 50

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This paper cites Fed- erated learning based on diffusion model to cope with non- iid data.

Federated Deconfounding and Debiasing Learning for Out-of-Distribution Generalization Fed- erated learning based on diffusion model to cope with non- iid data

Reference 51

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Observation 63d9dcf8-9833-42f8-a6d0-f13817fe609e · outbound

This paper cites Fedfa: Federated learning with feature anchors to align features and classifiers for heterogeneous data.

Federated Deconfounding and Debiasing Learning for Out-of-Distribution Generalization Fedfa: Federated learning with feature anchors to align features and classifiers for heterogeneous data

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:21:56.344862Z

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Observation 858f89a0-31c1-4ee2-84b9-fd799bc688ea · outbound

This paper cites Dualfed: enjoying both generalization and per- sonalization in federated learning via hierachical represen- tations.

Federated Deconfounding and Debiasing Learning for Out-of-Distribution Generalization Dualfed: enjoying both generalization and per- sonalization in federated learning via hierachical represen- tations

Reference 53

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Observation 09e338c0-a4b9-4fff-8bd9-df5c2ae375e2 · outbound

This paper cites FedCCRL: Federated Domain Generalization with Cross-Client Representation Learning.

Federated Deconfounding and Debiasing Learning for Out-of-Distribution Generalization FedCCRL: Federated Domain Generalization with Cross-Client Representation Learning

Reference 2008

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Observation 26c66b0d-e085-4289-99e5-fca3151deaff · outbound

This paper cites McKeown, and et al.

Federated Deconfounding and Debiasing Learning for Out-of-Distribution Generalization McKeown, and et al

Reference 2011

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Observation ebed50dd-bf45-4032-8de2-ada169f66b54 · outbound

This paper cites Gitfl: Uncertainty-aware real-time asynchronous federated learning using version control.

Federated Deconfounding and Debiasing Learning for Out-of-Distribution Generalization Gitfl: Uncertainty-aware real-time asynchronous federated learning using version control

Reference 2016

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Observation d49aa352-e4fe-45a6-91ff-8a6135743d30 · outbound

This paper cites Learn- ing using privileged information for food recognition.

Federated Deconfounding and Debiasing Learning for Out-of-Distribution Generalization Learn- ing using privileged information for food recognition

Reference 2017

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:21:56.819486Z

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Observation f1a43b37-8644-4096-92d9-61dc5f4db7b8 · outbound

This paper cites Improving global generalization and local personalization for federated learning.

Federated Deconfounding and Debiasing Learning for Out-of-Distribution Generalization Improving global generalization and local personalization for federated learning

Reference 2019

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:21:56.801656Z

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Observation 945ebe04-54e8-4de4-8fba-9c14d2121f78 · outbound

This paper cites Model-contrastive federated learning.

Federated Deconfounding and Debiasing Learning for Out-of-Distribution Generalization Model-contrastive federated learning

Reference 2020

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:21:56.921978Z

Source-reported events for the cited work

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Observation ca900789-294c-4ec5-803e-467c29caa0ee · outbound

This paper cites A swiss army knife for heterogeneous federated learning: Flexible coupling via trace norm.

Federated Deconfounding and Debiasing Learning for Out-of-Distribution Generalization A swiss army knife for heterogeneous federated learning: Flexible coupling via trace norm

Reference 2021

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:21:56.903897Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 1a46b916-f145-488c-b7ad-58593eb94cd2 · outbound

This paper cites Ten challenging problems in federated foundation models.

Federated Deconfounding and Debiasing Learning for Out-of-Distribution Generalization Ten challenging problems in federated foundation models

Reference 2022

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:21:57.308651Z

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Observation 686990d8-d2c6-4de4-b26d-bce8b478f114 · outbound

This paper cites Fair federated learning under domain skew with local consistency and domain diversity.

Federated Deconfounding and Debiasing Learning for Out-of-Distribution Generalization Fair federated learning under domain skew with local consistency and domain diversity

Reference 2023

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:21:57.353895Z

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Observation 0a7787de-f5c3-4867-8729-e61c949a6966 · outbound

This paper cites Federated domain generalization for image recognition via cross-client style transfer.

Federated Deconfounding and Debiasing Learning for Out-of-Distribution Generalization Federated domain generalization for image recognition via cross-client style transfer

Reference 2024

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:21:57.371040Z

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Observation b49bb4ce-28b7-45b9-8f9c-f071e99c77a5 · outbound

This paper cites Out-of-distribution generalization of federated learn- ing via implicit invariant relationships.

Federated Deconfounding and Debiasing Learning for Out-of-Distribution Generalization Out-of-distribution generalization of federated learn- ing via implicit invariant relationships

Reference 2025

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:21:57.189176Z

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Pith citing papers

Observation 397b00e7-b666-45ac-b71f-9d5435f19856 · inbound

Every Client Is an Environment: Federated De-confounding for Spatio-Temporal Forecasting cites this paper.

Every Client Is an Environment: Federated De-confounding for Spatio-Temporal Forecasting Federated Deconfounding and Debiasing Learning for Out-of-Distribution Generalization

Reference 29

Resolution: unresolved; no resolver link, observed 2026-07-31T20:45:27.138773Z

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Observation fa69818a-dec1-4db1-b76d-37a008e805f6 · inbound

Out-of-Distribution Federated Distillation with Domain-Aware Proxy cites this paper.

Out-of-Distribution Federated Distillation with Domain-Aware Proxy Federated Deconfounding and Debiasing Learning for Out-of-Distribution Generalization

Reference 2024

Resolution: metadata mismatch; local_arxiv, observed 2026-08-14T04:37:52.680206Z

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No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.