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Paper Citation Record · LEDGER

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

As of 19 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

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T23:21:56.082528Z

measured 55 of 55 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

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

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

No source-named external measurement is stored.

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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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 0c768a49-b590-4776-bc60-f047e07c2e24 · outbound

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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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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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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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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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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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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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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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 6753a111-e6b2-4c1d-8c2a-07483de4f975 · outbound

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

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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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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Source-reported events for the cited work

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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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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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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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Source-reported events for the cited work

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Observation 09c81fac-2caa-4e72-b5e3-3ec74c53c395 · outbound

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

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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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

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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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

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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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

Resolution
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Source-reported events for the cited work

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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

Resolution
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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 612ecdc8-8bda-4796-957b-b6c8af0399da · outbound

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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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation a27bf69d-09c4-4a69-be3b-52931794798f · outbound

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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Observation ad043874-6874-4464-b2c3-5cf3e098c43f · outbound

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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Source-reported events for the cited work

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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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Source-reported events for the cited work

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Observation 1c9d9f60-a99e-4ec2-9d04-5627a9830530 · outbound

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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Source-reported events for the cited work

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Observation b0a0c0b6-6668-4921-ac24-8664d90fff9f · outbound

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

Resolution
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Observation 4aff431b-05e2-4b7e-8d84-027197069bc9 · outbound

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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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation d62c447b-4491-45d9-bef6-b9097cac3faa · outbound

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

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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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

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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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

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 558a8199-9f3f-487a-a92f-47375cc89c55 · outbound

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

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation de601b5f-3342-48c6-a88b-33a1427f675e · outbound

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

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 87784547-c3d7-4f67-97d2-967edba7d581 · outbound

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

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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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

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation f27202c6-3f5b-4706-95a0-d5bcde473f83 · outbound

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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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation d7937b7b-9afc-4a3b-9ec9-948919a0bdca · outbound

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

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T23:21:56.484157Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T23:21:56.034869Z digest=sha256:e7c80c733b0629a48b76f5fd7c2ab94c6412a53b25e19b2e0b493c462bde7649

Observation 789188ed-dfad-4609-ba7e-1df6319c8a34 · outbound

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

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T23:21:56.467211Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T23:21:56.039818Z digest=sha256:8731ea72cce573659b5f6fe02f75bf73cfaba3de32bba97b42620bb5514c1cb0

Observation 7fbe1631-ac60-4ecb-8f88-e4e725afe81f · outbound

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

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T23:21:56.449495Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T23:21:56.044517Z digest=sha256:a887dc3547bcb0fb53ca9a23890f9cb03d11d5289c00ea1f171875fbdccaba06

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

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T23:21:56.432843Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T23:21:56.049104Z digest=sha256:ea03eff0e5d44ae836640058fc1997373ec44cd3be8fb2d6cb01f92a70849e0e

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

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T23:21:56.394548Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T23:21:56.058268Z digest=sha256:1227ffac7ce5a76a8aeb2c7ed65caf66cb1bf246005d76c92a77aff038b03ed1

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

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T23:21:56.377176Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T23:21:56.062664Z digest=sha256:c1aa2d164f47b298f996d36d8a49fbaa10a0e17b803cdb3b8aa6c20aa46b08b4

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

Resolution
unresolved
no resolver link, observed 2026-08-15T23:21:56.067929Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T23:21:56.067929Z digest=sha256:11b4e0b630a55ad22c78a9e95b1995daaa8c2366a9bec890d3f9a6e68b152ac3

Observation 6870c046-545a-47c8-9102-a04249d6ff85 · outbound

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

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T23:21:56.361082Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T23:21:56.073017Z digest=sha256:4b4be68f05e2f4d8c037df8045bbecf7c4ffb56ac9cb7dbfc16c5edb4d35f22f

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T23:21:56.077860Z digest=sha256:0682fca7d3d06df21ae380d0c6297119e613163eb6fb7643e449ab182fc2bc22

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

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T23:21:56.327819Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T23:21:56.082528Z digest=sha256:52f900cdc74dcafd13c86d64cb6569216dad79530c7bfd371ab8259e874b67c7

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

Resolution
verified exact
local_arxiv, observed 2026-08-15T23:21:56.145629Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T23:21:56.001732Z digest=sha256:29a3c154a6ebf3b2b55ac7fe997e541f0c53ca715662394d89ac9608823344ee

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

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T23:21:56.415153Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T23:21:56.053622Z digest=sha256:a95ac0b7fe7e159d10b24eed668463fc12344a5e81396d6c7e57a5ac672703c9

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

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T23:21:57.024267Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T23:21:55.858862Z digest=sha256:d4e98e0c58801c953a8f952523104035a62423d58dcef3e3040b4c78ae7b2719

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T23:21:55.919599Z digest=sha256:ace4b7d5e3168f263c657f617bc76de5b00148dad4a3010878fd4ab442b08678

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T23:21:55.924287Z digest=sha256:e739c60c42e55531e57983e38734452b1a975918361472c0c4cb8a144afb9291

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

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T23:21:55.883851Z digest=sha256:c9487cc5a728bed1e2416ee0963dd7f5090cc509810b7b4e2dd75e61ed7618f0

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T23:21:55.888712Z digest=sha256:6a59ee8bf77c817ad6486a95079b97037b5309ca934706306fa481cf644601bf

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T23:21:55.843579Z digest=sha256:685f28285e2e16f6112618defd9b61284605145beff33f34a8f126d7c491b96b

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T23:21:55.832849Z digest=sha256:d97a918ea1e92d3dcca1dc38e56f546434f38aa910b6df15b8677a5d2f41162d

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T23:21:55.827028Z digest=sha256:d9087be401074644209fd5818cd6d3c6f5ead370ced553fe6b8393bb2ba4de20

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T23:21:55.848795Z digest=sha256:81d0c647b86282888b21e657dd0d7ea32dee159dba7b1b908cdd65d1fa0d4fae

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-31T20:45:27.138773Z digest=sha256:8562db0f5315c9209126205a9d6353fc5fb53f0b3b576967f80843679e04b08c

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-14T04:37:52.592019Z digest=sha256:4ad0615f3a083178b07bc3e5272b9011998df4d2fae839a6cbc96d79ae0e0572