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Paper Citation Record · LEDGER

Federated Domain Generalization via Prompt Learning and Aggregation

As of 14 August 2026, this Paper Citation Record lists 56 of 56 outbound references and 0 inbound Pith citation observations for arXiv:2411.10063.

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

pith.paper-citation-record.v1
2411.10063 v1

Coverage vector

measured 56 of 56 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-12T20:05:06.886010Z

measured 56 of 56 standing notices

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Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

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measured 0 of 1 external citation measurements

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Source: cited_works

Reference resolution

56 of 56 outbound references displayed

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  • verified fuzzy20
  • unresolved34
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External citation measurements

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Outbound references

Observation 59bfea05-9a44-4429-9dbc-0b601e60eb99 · outbound

This paper cites Communication-efficient learning of deep networks from decentralized data,.

Federated Domain Generalization via Prompt Learning and Aggregation Communication-efficient learning of deep networks from decentralized data,

Reference 1

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Observation 48aab3c7-18d7-4812-919d-d706bf2acb77 · outbound

This paper cites Federated learning with differential privacy: Algorithms and performance analysis,.

Federated Domain Generalization via Prompt Learning and Aggregation Federated learning with differential privacy: Algorithms and performance analysis,

Reference 2

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Observation 9b582a3e-110a-4494-9eec-e92ece815206 · outbound

This paper cites Federated optimization in heterogeneous networks,.

Federated Domain Generalization via Prompt Learning and Aggregation Federated optimization in heterogeneous networks,

Reference 3

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Observation 92e183c5-19f7-47a2-abe2-c7ad14e0028b · outbound

This paper cites Tackling the objective inconsistency problem in heterogeneous federated optimiza- tion,.

Federated Domain Generalization via Prompt Learning and Aggregation Tackling the objective inconsistency problem in heterogeneous federated optimiza- tion,

Reference 4

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Observation 5afb9c8a-0a5a-466c-93d0-dcea504a251f · outbound

This paper cites Scaffold: Stochastic controlled averaging for federated learn- ing,.

Federated Domain Generalization via Prompt Learning and Aggregation Scaffold: Stochastic controlled averaging for federated learn- ing,

Reference 5

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Observation 2a39aed9-ebf0-4532-b30f-dde7c0fc7590 · outbound

This paper cites Harmofl: Harmonizing local and global drifts in federated learning on heterogeneous medical images,.

Federated Domain Generalization via Prompt Learning and Aggregation Harmofl: Harmonizing local and global drifts in federated learning on heterogeneous medical images,

Reference 6

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Observation c766d9b7-309e-455a-aa68-7ab8ac4e608a · outbound

This paper cites Domain generalization for face anti-spoofing via negative data augmentation,.

Federated Domain Generalization via Prompt Learning and Aggregation Domain generalization for face anti-spoofing via negative data augmentation,

Reference 7

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Observation dc992af1-d58c-482c-9bb8-9107403d9c97 · outbound

This paper cites Mixstyle neural networks for domain generalization and adaptation,.

Federated Domain Generalization via Prompt Learning and Aggregation Mixstyle neural networks for domain generalization and adaptation,

Reference 8

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Observation b5b86c1a-c930-4a34-8ded-08d25f34297a · outbound

This paper cites Feddg: Federated do- main generalization on medical image segmentation via episodic learn- ing in continuous frequency space,.

Federated Domain Generalization via Prompt Learning and Aggregation Feddg: Federated do- main generalization on medical image segmentation via episodic learn- ing in continuous frequency space,

Reference 9

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Observation b7eedad5-446d-45e9-b630-fc0cd91aa85a · outbound

This paper cites Rethinking federated learning with domain shift: A prototype view,.

Federated Domain Generalization via Prompt Learning and Aggregation Rethinking federated learning with domain shift: A prototype view,

Reference 10

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Observation 7c7a9617-b51d-4f69-a16c-9d820c00956f · outbound

This paper cites Federated domain generaliza- tion for image recognition via cross-client style transfer,.

Federated Domain Generalization via Prompt Learning and Aggregation Federated domain generaliza- tion for image recognition via cross-client style transfer,

Reference 11

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Observation 11ccaec2-215b-417f-b4d7-1e37f91b85d2 · outbound

This paper cites Federated Learning with Domain Generalization.

Federated Domain Generalization via Prompt Learning and Aggregation Federated Learning with Domain Generalization

Reference 12

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Observation ef54af02-5f9b-4063-ad96-4f1523194be6 · outbound

This paper cites Learning transferable visual models from natural language supervision,.

Federated Domain Generalization via Prompt Learning and Aggregation Learning transferable visual models from natural language supervision,

Reference 13

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Observation 0d035cca-c44a-44be-89d7-ed8bfaca9f62 · outbound

This paper cites Blip: Bootstrapping language-image pre-training for unified vision-language understanding and generation,.

Federated Domain Generalization via Prompt Learning and Aggregation Blip: Bootstrapping language-image pre-training for unified vision-language understanding and generation,

Reference 14

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Observation 67ad6e20-badb-41f8-b3f3-ea1659cdf21b · outbound

This paper cites Learning to prompt for vision- language models,.

Federated Domain Generalization via Prompt Learning and Aggregation Learning to prompt for vision- language models,

Reference 15

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Observation e5b0eb45-aad4-44be-9cc8-e0f8aa79b925 · outbound

This paper cites Maple: Multi-modal prompt learning,.

Federated Domain Generalization via Prompt Learning and Aggregation Maple: Multi-modal prompt learning,

Reference 16

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Observation 81a30472-30e1-4eeb-bf73-8431c5732559 · outbound

This paper cites Promptfl: Let federated participants cooperatively learn prompts instead of models-federated learning in age of foundation model,.

Federated Domain Generalization via Prompt Learning and Aggregation Promptfl: Let federated participants cooperatively learn prompts instead of models-federated learning in age of foundation model,

Reference 17

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Observation 0f9b68a8-e4e4-4cdd-b0d0-60bdd2877213 · outbound

This paper cites Learning federated visual prompt in null space for mri reconstruction,.

Federated Domain Generalization via Prompt Learning and Aggregation Learning federated visual prompt in null space for mri reconstruction,

Reference 18

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Observation 977d1fa9-ea25-457f-a877-a2ea12048dd8 · outbound

This paper cites What do we mean by generalization in federated learning?.

Federated Domain Generalization via Prompt Learning and Aggregation What do we mean by generalization in federated learning?

Reference 19

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Observation 2454e1f0-f07c-4ff7-81aa-e2d3a400ae94 · outbound

This paper cites Model-contrastive federated learning,.

Federated Domain Generalization via Prompt Learning and Aggregation Model-contrastive federated learning,

Reference 20

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Observation 4a368d8a-98f6-480d-acd8-bfac75c3f874 · outbound

This paper cites FedBN: Federated Learning on Non-IID Features via Local Batch Normalization.

Federated Domain Generalization via Prompt Learning and Aggregation FedBN: Federated Learning on Non-IID Features via Local Batch Normalization

Reference 21

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Observation 8d2f96f6-193f-4027-9e10-276b0693a6fc · outbound

This paper cites Adaptive Federated Optimization.

Federated Domain Generalization via Prompt Learning and Aggregation Adaptive Federated Optimization

Reference 22

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Observation 099af462-9162-402d-9ee5-203fd1076774 · outbound

This paper cites Madg: Margin-based adversarial learning for domain generalization,.

Federated Domain Generalization via Prompt Learning and Aggregation Madg: Margin-based adversarial learning for domain generalization,

Reference 23

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Observation f8b6e5ca-9fff-43ee-b15f-a02a0943d586 · outbound

This paper cites Diversifying spatial-temporal perception for video domain generalization,.

Federated Domain Generalization via Prompt Learning and Aggregation Diversifying spatial-temporal perception for video domain generalization,

Reference 24

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Observation f35b9893-1e7f-4e6f-9178-f4e62e5701e1 · outbound

This paper cites Robust domain misinformation detection via multi-modal feature alignment,.

Federated Domain Generalization via Prompt Learning and Aggregation Robust domain misinformation detection via multi-modal feature alignment,

Reference 25

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Observation 319e8d39-9a55-4140-8f7c-f1b1c0de54b2 · outbound

This paper cites Learning to generalize: Meta-learning for domain generalization,.

Federated Domain Generalization via Prompt Learning and Aggregation Learning to generalize: Meta-learning for domain generalization,

Reference 26

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Observation 7278acc7-abf6-43fe-90b5-696380b60741 · outbound

This paper cites Bi-level meta-learning for few-shot domain generalization,.

Federated Domain Generalization via Prompt Learning and Aggregation Bi-level meta-learning for few-shot domain generalization,

Reference 27

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Observation d1efb127-c7bc-46c5-8e16-2e9930d6f843 · outbound

This paper cites Federated Domain Generalization: A Survey.

Federated Domain Generalization via Prompt Learning and Aggregation Federated Domain Generalization: A Survey

Reference 28

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Observation 27ec94b7-23a3-4865-a490-ce6ec98a1913 · outbound

This paper cites Conditional prompt learning for vision-language models,.

Federated Domain Generalization via Prompt Learning and Aggregation Conditional prompt learning for vision-language models,

Reference 29

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Observation 734a6d15-a59a-49c9-abda-057389d6a4e9 · outbound

This paper cites Self-regulating prompts: Foundational model adaptation without 13 forgetting,.

Federated Domain Generalization via Prompt Learning and Aggregation Self-regulating prompts: Foundational model adaptation without 13 forgetting,

Reference 30

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Observation 64bce8b0-b894-4a58-8efa-2d8fdba11621 · outbound

This paper cites DiPrompT: Disentangled Prompt Tuning for Multiple Latent Domain Generalization in Federated Learning.

Federated Domain Generalization via Prompt Learning and Aggregation DiPrompT: Disentangled Prompt Tuning for Multiple Latent Domain Generalization in Federated Learning

Reference 31

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Observation b5676c67-dc2d-47e3-8125-65cc94b2cca3 · outbound

This paper cites Attention is all you need,.

Federated Domain Generalization via Prompt Learning and Aggregation Attention is all you need,

Reference 32

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Observation 7299f95c-2376-4ca8-bcb9-d5d79351f930 · outbound

This paper cites An image is worth 16x16 words: Transformers for image recognition at scale,.

Federated Domain Generalization via Prompt Learning and Aggregation An image is worth 16x16 words: Transformers for image recognition at scale,

Reference 33

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Observation 35d22228-6443-4ebc-aae2-af97d89500b8 · outbound

This paper cites Simcls: A simple framework for contrastive learning of abstractive summarization,.

Federated Domain Generalization via Prompt Learning and Aggregation Simcls: A simple framework for contrastive learning of abstractive summarization,

Reference 34

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Observation 08cf55a6-19cb-41d3-a5fb-4e3b01b84099 · outbound

This paper cites Visual prompt tuning,.

Federated Domain Generalization via Prompt Learning and Aggregation Visual prompt tuning,

Reference 35

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Observation 051e1676-02fb-4be3-9e88-2056e3b6d42b · outbound

This paper cites Hard prompts made easy: Gradient-based discrete optimization for prompt tuning and discovery,.

Federated Domain Generalization via Prompt Learning and Aggregation Hard prompts made easy: Gradient-based discrete optimization for prompt tuning and discovery,

Reference 36

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Observation 8a4ceab1-a1a1-48a8-a278-ea733edc62f0 · outbound

This paper cites Federated adaptive prompt tuning for multi-domain collaborative learning,.

Federated Domain Generalization via Prompt Learning and Aggregation Federated adaptive prompt tuning for multi-domain collaborative learning,

Reference 37

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raw_fallback, observed 2026-08-12T20:05:07.301538Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-12T20:05:06.805993Z digest=sha256:8e0f21d3e79f750a17536722e75a3b1e8943b947120fe021bf01e3b7ae9c9e95

Observation 2dc37cca-e287-4e91-84eb-3fd9a6bf5d2b · outbound

This paper cites On information and sufficiency,.

Federated Domain Generalization via Prompt Learning and Aggregation On information and sufficiency,

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T20:05:07.286870Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-12T20:05:06.809902Z digest=sha256:6ecf1b70f47ea0415cbd5960c5ee26ee70a299a048f5787dcabbc292cbd982cc

Observation e437143c-5e28-49de-bb33-d21c6cdff6cb · outbound

This paper cites Revisiting knowledge distillation via label smoothing regularization,.

Federated Domain Generalization via Prompt Learning and Aggregation Revisiting knowledge distillation via label smoothing regularization,

Reference 39

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no resolver link, observed 2026-08-12T20:05:06.813997Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T20:05:06.813997Z digest=sha256:87c1f4ad331c70ac3b57091db9d8fb8b03a9ca78b53f85adfc812229761eb057

Observation 5fd6c36c-82be-4c36-bf65-57de72e47af8 · outbound

This paper cites Deep residual learning for image recognition,.

Federated Domain Generalization via Prompt Learning and Aggregation Deep residual learning for image recognition,

Reference 40

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unresolved
no resolver link, observed 2026-08-12T20:05:06.818083Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T20:05:06.818083Z digest=sha256:4e9ce5ab6f18a479e0599eded2ea823897a072a2cafd72aa9a9aaa7775f5fce4

Observation 14a5e749-2e92-49f6-b908-a670a937caa7 · outbound

This paper cites Deeper, broader and artier domain generalization,.

Federated Domain Generalization via Prompt Learning and Aggregation Deeper, broader and artier domain generalization,

Reference 41

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unresolved
no resolver link, observed 2026-08-12T20:05:06.821858Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T20:05:06.821858Z digest=sha256:1c318e92c0bf797ed9034f38606c5f4a34c863d72832b6323889428d450832a9

Observation 79bd93d8-f25c-4b09-bdd3-d642354d3841 · outbound

This paper cites Deep hashing network for unsupervised domain adaptation,.

Federated Domain Generalization via Prompt Learning and Aggregation Deep hashing network for unsupervised domain adaptation,

Reference 42

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no resolver link, observed 2026-08-12T20:05:06.825933Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T20:05:06.825933Z digest=sha256:1483afdabd27ab4b9c282208d05bc5953732772a958498b4caa9c32ecd71fabc

Observation b4543764-1045-44e3-b1bc-59d68c91d381 · outbound

This paper cites Unbiased metric learning: On the utilization of multiple datasets and web images for softening bias,.

Federated Domain Generalization via Prompt Learning and Aggregation Unbiased metric learning: On the utilization of multiple datasets and web images for softening bias,

Reference 43

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no resolver link, observed 2026-08-12T20:05:06.829864Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T20:05:06.829864Z digest=sha256:6671809c7afc270d245d82a3094fa412731761233149b6329c73f8f1a8add759

Observation 4fc05618-76a6-41fd-921e-e925d86d496a · outbound

This paper cites Moment matching for multi-source domain adaptation,.

Federated Domain Generalization via Prompt Learning and Aggregation Moment matching for multi-source domain adaptation,

Reference 44

Resolution
unresolved
no resolver link, observed 2026-08-12T20:05:06.834186Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T20:05:06.834186Z digest=sha256:f0ad6d4d777fd8a2503ff9762cd4da4720dbac7da52bb6826843043c90080058

Observation b887fa04-01f0-4457-af46-a6f7326eeb90 · outbound

This paper cites Federated domain generalization with generalization adjustment,.

Federated Domain Generalization via Prompt Learning and Aggregation Federated domain generalization with generalization adjustment,

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T20:05:07.215571Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-12T20:05:06.838419Z digest=sha256:480391aa34bcb80c9054f1e7b158fcd6f39a65159ae333dfb1adfd76f892ace3

Observation ed9d7911-7fe8-46a5-9120-d6e614ed246b · outbound

This paper cites In search of lost domain generalization,.

Federated Domain Generalization via Prompt Learning and Aggregation In search of lost domain generalization,

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T20:05:07.201920Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-12T20:05:06.842603Z digest=sha256:bab6869d1d2765f0d7dc3be9e00885f0840bb3213052482320b81621374fc9f7

Observation d1e9076b-62c1-4e39-93d7-7fde240bc98b · outbound

This paper cites Self-challenging im- proves cross-domain generalization,.

Federated Domain Generalization via Prompt Learning and Aggregation Self-challenging im- proves cross-domain generalization,

Reference 47

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verified fuzzy
raw_fallback, observed 2026-08-12T20:05:07.188026Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-12T20:05:06.846778Z digest=sha256:309f867a68f722c03e40265b82599946dd6c14025dfc206eeaaa28b9dc4b395b

Observation d6db9517-5e41-471d-b8ac-9437b39d0b82 · outbound

This paper cites A fourier-based framework for domain generalization,.

Federated Domain Generalization via Prompt Learning and Aggregation A fourier-based framework for domain generalization,

Reference 48

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no resolver link, observed 2026-08-12T20:05:06.851069Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T20:05:06.851069Z digest=sha256:1cdfef63853ca9a0a0f7e3602f7464e1771142e28d7e695ea98c012043676b5e

Observation d83f8f0a-9578-45f0-a0b5-a8407cc0a841 · outbound

This paper cites Swad: Domain generalization by seeking flat minima,.

Federated Domain Generalization via Prompt Learning and Aggregation Swad: Domain generalization by seeking flat minima,

Reference 49

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-12T20:05:06.855232Z digest=sha256:74c12bcb23cda82943c13e7ea446bd40f22886d8423da16a6e7456a77aa1fcbd

Observation 97d3e000-0777-42b5-8e24-63bb7335b836 · outbound

This paper cites Hcvp: Leveraging hierarchical contrastive visual prompt for domain generalization,.

Federated Domain Generalization via Prompt Learning and Aggregation Hcvp: Leveraging hierarchical contrastive visual prompt for domain generalization,

Reference 50

Resolution
verified exact
raw_fallback, observed 2026-08-12T20:05:07.012895Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-12T20:05:06.859489Z digest=sha256:8a13d059aa9ebc1a1a509a37d7bc66c99f8306c411d183eb1574d243151c7470

Observation 50c4fef2-080d-4931-8abf-d58e992b8cd9 · outbound

This paper cites Prompt Vision Transformer for Domain Generalization.

Federated Domain Generalization via Prompt Learning and Aggregation Prompt Vision Transformer for Domain Generalization

Reference 51

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-12T20:05:06.863943Z digest=sha256:590634791576785752b805da5ea258e3004cb502cc464a34949988119516e810

Observation 1a8fc1f9-4cf2-4f48-a717-cc48d17fc61d · outbound

This paper cites Fedsr: A simple and effective domain generalization method for federated learning,.

Federated Domain Generalization via Prompt Learning and Aggregation Fedsr: A simple and effective domain generalization method for federated learning,

Reference 52

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T20:05:07.155017Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-12T20:05:06.868884Z digest=sha256:7f7d9c6818715c9f995daaaae3a45927211c02dd1e3b249510ffc11956f414a0

Observation ab652d0f-f7c9-40cc-82dc-ceaa1cd61c2e · outbound

This paper cites Fedclip: Fast generalization and personalization for clip in federated learning,.

Federated Domain Generalization via Prompt Learning and Aggregation Fedclip: Fast generalization and personalization for clip in federated learning,

Reference 53

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T20:05:07.140562Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-12T20:05:06.873142Z digest=sha256:55362aa00c4e3c596817e29ffef64f04b30fcf84e8c949cdbb64c09f0b430132

Observation 5627f871-589c-41f3-a901-0e441dd945be · outbound

This paper cites Dualprompt: Complementary prompting for rehearsal-free continual learning,.

Federated Domain Generalization via Prompt Learning and Aggregation Dualprompt: Complementary prompting for rehearsal-free continual learning,

Reference 54

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T20:05:06.877378Z digest=sha256:f1d0ebd98c2b500af2b1187b1257f3306eb8cd5e37b997fd57728d175d394804

Observation 9e3b50bf-8b73-4fce-a703-d9b89fed0db5 · outbound

This paper cites Visualizing data using t-sne.

Federated Domain Generalization via Prompt Learning and Aggregation Visualizing data using t-sne

Reference 55

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source=pdf_text observed=2026-08-12T20:05:06.881569Z digest=sha256:60d4eab6a62de479dc51b3622c40785995d37ccf278da74ccb27aeb8a28a3127

Observation 2037327e-c1a6-48de-a207-c0930d357dba · outbound

This paper cites Learning deep features for discriminative localization,.

Federated Domain Generalization via Prompt Learning and Aggregation Learning deep features for discriminative localization,

Reference 56

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T20:05:06.886010Z digest=sha256:eaa52e68f82269f23f67cc31f7ffbaef1a1e5c9a339c96d21f0450321b693255

Pith citing papers

No inbound Pith citation observations are available.