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Paper Citation Record · LEDGER

FixCLR: Negative-Class Contrastive Learning for Semi-Supervised Domain Generalization

As of 8 August 2026, this Paper Citation Record lists 45 of 45 outbound references and 0 inbound Pith citation observations for arXiv:2506.20841.

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

pith.paper-citation-record.v1
2506.20841 v1

Coverage vector

measured 45 of 45 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T22:44:07.011458Z

measured 45 of 45 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

45 of 45 outbound references displayed

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  • verified fuzzy34
  • unresolved10
  • parse uncertain0
  • malformed identifier0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 82c67f76-e62b-40d8-94a6-5da8c5183376 · outbound

This paper cites Recognition in terra incognita.

FixCLR: Negative-Class Contrastive Learning for Semi-Supervised Domain Generalization Recognition in terra incognita

Reference 1

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Observation c56ec553-f4d5-422b-9fa0-2fc3be428e6a · outbound

This paper cites Curriculum learning.

FixCLR: Negative-Class Contrastive Learning for Semi-Supervised Domain Generalization Curriculum learning

Reference 2

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Observation a9a17e41-64cd-49cc-b307-92b8d4715231 · outbound

This paper cites Detecting racism and xenophobia using deep learning models on twitter data: Cnn, lstm and bert.

FixCLR: Negative-Class Contrastive Learning for Semi-Supervised Domain Generalization Detecting racism and xenophobia using deep learning models on twitter data: Cnn, lstm and bert

Reference 3

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Observation 22d0545d-4123-48e9-be43-a5f29fa2af4b · outbound

This paper cites ReMixMatch: Semi-Supervised Learning with Distribution Alignment and Augmentation Anchoring.

FixCLR: Negative-Class Contrastive Learning for Semi-Supervised Domain Generalization ReMixMatch: Semi-Supervised Learning with Distribution Alignment and Augmentation Anchoring

Reference 4

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Observation d3841777-8d06-4403-8a89-1b7b7adb32f5 · outbound

This paper cites Mixmatch: A holistic approach to semi-supervised learning.

FixCLR: Negative-Class Contrastive Learning for Semi-Supervised Domain Generalization Mixmatch: A holistic approach to semi-supervised learning

Reference 5

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Observation 2b6611cd-413c-4b15-9b8c-87cc0a5cb3d5 · outbound

This paper cites SoftMatch: Addressing the Quantity-Quality Trade-off in Semi-supervised Learning.

FixCLR: Negative-Class Contrastive Learning for Semi-Supervised Domain Generalization SoftMatch: Addressing the Quantity-Quality Trade-off in Semi-supervised Learning

Reference 6

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Observation 032d9f52-f84a-46b3-b70c-04132f92205b · outbound

This paper cites A simple framework for contrastive learning of visual representations.

FixCLR: Negative-Class Contrastive Learning for Semi-Supervised Domain Generalization A simple framework for contrastive learning of visual representations

Reference 7

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Observation 7a7d2b4b-134f-450c-9ce2-bc9748b6c3e7 · outbound

This paper cites Big self-supervised models are strong semi-supervised learners.

FixCLR: Negative-Class Contrastive Learning for Semi-Supervised Domain Generalization Big self-supervised models are strong semi-supervised learners

Reference 8

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Observation 5204fe1a-960a-4062-b913-2438cfdebdca · outbound

This paper cites Can ai be racist? color-evasiveness in the appli- cation of machine learning to science assessments.

FixCLR: Negative-Class Contrastive Learning for Semi-Supervised Domain Generalization Can ai be racist? color-evasiveness in the appli- cation of machine learning to science assessments

Reference 9

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Source-reported events for the cited work

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Observation 8d129531-3337-459f-aedf-d8767ff35c57 · outbound

This paper cites A brief review of domain adaptation.

FixCLR: Negative-Class Contrastive Learning for Semi-Supervised Domain Generalization A brief review of domain adaptation

Reference 10

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Observation a57541b1-18ba-4f9e-9e99-9743b2307f82 · outbound

This paper cites Towards Generalizing to Unseen Domains with Few Labels.

FixCLR: Negative-Class Contrastive Learning for Semi-Supervised Domain Generalization Towards Generalizing to Unseen Domains with Few Labels

Reference 11

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Observation 7914d3c8-7359-4c42-a284-42a8f741fc35 · outbound

This paper cites Semi-supervised learning by entropy minimization.

FixCLR: Negative-Class Contrastive Learning for Semi-Supervised Domain Generalization Semi-supervised learning by entropy minimization

Reference 12

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 6d1a6940-85bc-4d79-b2d7-a3910d41d7ca · outbound

This paper cites Bootstrap your own latent-a new approach to self-supervised learning.

FixCLR: Negative-Class Contrastive Learning for Semi-Supervised Domain Generalization Bootstrap your own latent-a new approach to self-supervised learning

Reference 13

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Observation 27443b6d-dc71-4d2e-a1ec-0e6ffe84f64f · outbound

This paper cites The many faces of robust- ness: A critical analysis of out-of-distribution generalization.

FixCLR: Negative-Class Contrastive Learning for Semi-Supervised Domain Generalization The many faces of robust- ness: A critical analysis of out-of-distribution generalization

Reference 14

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 5e0f0c65-5842-44f2-a82c-32bc01ba0792 · outbound

This paper cites Category contrast for unsupervised domain adap- tation in visual tasks.

FixCLR: Negative-Class Contrastive Learning for Semi-Supervised Domain Generalization Category contrast for unsupervised domain adap- tation in visual tasks

Reference 15

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 672dcf56-02a9-4226-bc63-9ebd590ee198 · outbound

This paper cites Arbitrary style transfer in real-time with adaptive instance normalization.

FixCLR: Negative-Class Contrastive Learning for Semi-Supervised Domain Generalization Arbitrary style transfer in real-time with adaptive instance normalization

Reference 16

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Observation 744fbe6a-4222-4733-96c9-ff8aae4c5759 · outbound

This paper cites Selfreg: Self-supervised contrastive regu- larization for domain generalization.

FixCLR: Negative-Class Contrastive Learning for Semi-Supervised Domain Generalization Selfreg: Self-supervised contrastive regu- larization for domain generalization

Reference 17

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 70134f3a-40dd-44e5-9887-1f39d8d18b8f · outbound

This paper cites Nlnl: Negative learning for noisy labels.

FixCLR: Negative-Class Contrastive Learning for Semi-Supervised Domain Generalization Nlnl: Negative learning for noisy labels

Reference 18

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 8cb669eb-4f0f-4745-9c65-2ab70e24265f · outbound

This paper cites Joint negative and positive learning for noisy labels.

FixCLR: Negative-Class Contrastive Learning for Semi-Supervised Domain Generalization Joint negative and positive learning for noisy labels

Reference 19

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation c3a863cf-7a29-4804-9606-0aba3b50a641 · outbound

This paper cites Wilds: A benchmark of in-the- wild distribution shifts.

FixCLR: Negative-Class Contrastive Learning for Semi-Supervised Domain Generalization Wilds: A benchmark of in-the- wild distribution shifts

Reference 20

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 6ced8b1f-c349-4a85-b1c8-483131d4602c · outbound

This paper cites Temporal Ensembling for Semi-Supervised Learning.

FixCLR: Negative-Class Contrastive Learning for Semi-Supervised Domain Generalization Temporal Ensembling for Semi-Supervised Learning

Reference 21

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Observation abfd419f-d46e-4880-9e40-f4a61bf1919b · outbound

This paper cites Deep learning.

FixCLR: Negative-Class Contrastive Learning for Semi-Supervised Domain Generalization Deep learning

Reference 22

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Observation d0ab301b-be55-4b83-8c6c-e8882206612f · outbound

This paper cites Pseudo-label: The simple and effi- cient semi-supervised learning method for deep neural net- works.

FixCLR: Negative-Class Contrastive Learning for Semi-Supervised Domain Generalization Pseudo-label: The simple and effi- cient semi-supervised learning method for deep neural net- works

Reference 23

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 4fedd330-35b9-4f7f-be9f-2e64032947b4 · outbound

This paper cites Improving domain generalization in contrastive learning using domain-aware temperature control.

FixCLR: Negative-Class Contrastive Learning for Semi-Supervised Domain Generalization Improving domain generalization in contrastive learning using domain-aware temperature control

Reference 24

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation e4ac74e4-a3e2-47d9-98eb-a867b9a16e40 · outbound

This paper cites Deeper, broader and artier domain generaliza- tion.

FixCLR: Negative-Class Contrastive Learning for Semi-Supervised Domain Generalization Deeper, broader and artier domain generaliza- tion

Reference 25

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 6bc6512d-fa6c-4fd9-bf7d-a5ff54b9b6e4 · outbound

This paper cites Berg, and 9 Li Fei-Fei.

FixCLR: Negative-Class Contrastive Learning for Semi-Supervised Domain Generalization Berg, and 9 Li Fei-Fei

Reference 26

Resolution
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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 47b8c5f1-ce24-458a-a003-64adfb5a077c · outbound

This paper cites Regularization with stochastic transformations and perturba- tions for deep semi-supervised learning.

FixCLR: Negative-Class Contrastive Learning for Semi-Supervised Domain Generalization Regularization with stochastic transformations and perturba- tions for deep semi-supervised learning

Reference 27

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 2255c0c6-28bd-43aa-a830-08d84ef6b64e · outbound

This paper cites Don’t fear the unlabelled: safe semi-supervised learning via debiasing.

FixCLR: Negative-Class Contrastive Learning for Semi-Supervised Domain Generalization Don’t fear the unlabelled: safe semi-supervised learning via debiasing

Reference 28

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 0973fd63-5f2c-482b-8abd-392589ea2b55 · outbound

This paper cites Generalizing Across Domains via Cross-Gradient Training.

FixCLR: Negative-Class Contrastive Learning for Semi-Supervised Domain Generalization Generalizing Across Domains via Cross-Gradient Training

Reference 29

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Unavailable: canonical work link unavailable.

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Observation c019468d-d2ee-4a23-bdbd-c76346a6ab4c · outbound

This paper cites Clda: Contrastive learning for semi-supervised domain adaptation.

FixCLR: Negative-Class Contrastive Learning for Semi-Supervised Domain Generalization Clda: Contrastive learning for semi-supervised domain adaptation

Reference 30

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 448367ce-044e-40e2-9236-5f6cf857c366 · outbound

This paper cites Fixmatch: Simplifying semi-supervised learning with consistency and confidence.

FixCLR: Negative-Class Contrastive Learning for Semi-Supervised Domain Generalization Fixmatch: Simplifying semi-supervised learning with consistency and confidence

Reference 31

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 9ca55f31-f831-410d-afc8-54450381d79d · outbound

This paper cites Resnet in Resnet: Generalizing Residual Architectures.

FixCLR: Negative-Class Contrastive Learning for Semi-Supervised Domain Generalization Resnet in Resnet: Generalizing Residual Architectures

Reference 32

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Unavailable: canonical work link unavailable.

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Observation 4a47f852-ca9d-44f1-b859-5a6f6a2eab56 · outbound

This paper cites Deep hashing network for unsupervised domain adaptation.

FixCLR: Negative-Class Contrastive Learning for Semi-Supervised Domain Generalization Deep hashing network for unsupervised domain adaptation

Reference 33

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 74c9b5b7-39a6-4a5b-8b4b-4f1937f53cc5 · outbound

This paper cites Learning robust global representations by penalizing local predictive power.

FixCLR: Negative-Class Contrastive Learning for Semi-Supervised Domain Generalization Learning robust global representations by penalizing local predictive power

Reference 34

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 3c17716b-abde-4bdc-9738-a51faaea2160 · outbound

This paper cites Generalizing to unseen domains: A survey on do- main generalization.

FixCLR: Negative-Class Contrastive Learning for Semi-Supervised Domain Generalization Generalizing to unseen domains: A survey on do- main generalization

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:44:09.055653Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T22:44:06.346560Z digest=sha256:c8ee2ceed093532ed364d1152d50118fad64bf57a2740bc66af6507897f02e92

Observation 9db033b5-23e6-4d9b-b0c1-2bd3b882c035 · outbound

This paper cites Debiased learning from naturally imbalanced pseudo-labels.

FixCLR: Negative-Class Contrastive Learning for Semi-Supervised Domain Generalization Debiased learning from naturally imbalanced pseudo-labels

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:44:08.879080Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T22:44:06.431883Z digest=sha256:037fb95eb7df5556b8c1a8a1b3213b13868c98188966674ddd627f3a4c973548

Observation f803315f-949e-4444-8235-3988977e0db3 · outbound

This paper cites FreeMatch: Self-adaptive Thresholding for Semi-supervised Learning.

FixCLR: Negative-Class Contrastive Learning for Semi-Supervised Domain Generalization FreeMatch: Self-adaptive Thresholding for Semi-supervised Learning

Reference 37

Resolution
unresolved
no resolver link, observed 2026-08-06T22:44:06.497039Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:44:06.497039Z digest=sha256:e2d64f7c99c71987a52d47092c95cadd0e1dfa27d80f972f65389e6fae7455ed

Observation 9e81bedf-1b24-4dda-8df7-d976e65c4d4e · outbound

This paper cites Revisiting pretraining for semi- supervised learning in the low-label regime.

FixCLR: Negative-Class Contrastive Learning for Semi-Supervised Domain Generalization Revisiting pretraining for semi- supervised learning in the low-label regime

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:44:08.668382Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T22:44:06.560694Z digest=sha256:bc88cf57796773b020107ed2911347b4348c6f950e546c3c72bc6cf2d941ddc2

Observation 962cddb3-8562-4205-8441-3901a06ed347 · outbound

This paper cites Pcl: Proxy-based contrastive learning for domain generalization.

FixCLR: Negative-Class Contrastive Learning for Semi-Supervised Domain Generalization Pcl: Proxy-based contrastive learning for domain generalization

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:44:08.432065Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T22:44:06.623466Z digest=sha256:92d444ff9979f4f4a056e20d353ef3be18dc7e40b0951a74ce28ed5236dd8552

Observation 6e344600-4c44-495d-9580-02ea88dd09b6 · outbound

This paper cites Rethinking the evaluation protocol of domain generalization.

FixCLR: Negative-Class Contrastive Learning for Semi-Supervised Domain Generalization Rethinking the evaluation protocol of domain generalization

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:44:08.272445Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T22:44:06.680678Z digest=sha256:d3145fefc07d3e7ed2cf000cd74e93e55d2b65479e8834b13ce158bd8f8528f9

Observation 7d693c50-f7c7-41f4-812e-9652ea41891d · outbound

This paper cites Flexmatch: Boosting semi-supervised learning with curricu- lum pseudo labeling.

FixCLR: Negative-Class Contrastive Learning for Semi-Supervised Domain Generalization Flexmatch: Boosting semi-supervised learning with curricu- lum pseudo labeling

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:44:08.099498Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T22:44:06.752562Z digest=sha256:e47b66ab72a0732c36894d4a424d5f9247dc97b86fd41d941a041c730ce031e8

Observation b8145415-55cb-4829-80ac-9ae7e94923ed · outbound

This paper cites Deep domain-adversarial image generation for do- main generalisation.

FixCLR: Negative-Class Contrastive Learning for Semi-Supervised Domain Generalization Deep domain-adversarial image generation for do- main generalisation

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:44:07.916486Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T22:44:06.817668Z digest=sha256:bf85ea934aff9422a46701698937c5cc9f2fb80f23bbd49cea31c23f06907420

Observation d498f3d8-9630-4e50-a36b-3f955ce31626 · outbound

This paper cites Deep domain-adversarial image generation for do- main generalisation.

FixCLR: Negative-Class Contrastive Learning for Semi-Supervised Domain Generalization Deep domain-adversarial image generation for do- main generalisation

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:44:07.745570Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T22:44:06.862766Z digest=sha256:70bec9b3b25338e512ef56952dd6cea4ba4bb48709a94db3554f2456d7cdc1dd

Observation 6703b392-5eaf-4f8a-bde9-6c34284e568a · outbound

This paper cites Domain generalization: A survey.

FixCLR: Negative-Class Contrastive Learning for Semi-Supervised Domain Generalization Domain generalization: A survey

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:44:07.566343Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T22:44:06.940530Z digest=sha256:82f9c68154327c0fe9f49436ec9c983924f7d4073b70cb7cb2d50554446cd48a

Observation ea7acea4-5594-42ce-a4cc-f259ffbaee5a · outbound

This paper cites Semi-supervised domain generalization with stochastic stylematch.

FixCLR: Negative-Class Contrastive Learning for Semi-Supervised Domain Generalization Semi-supervised domain generalization with stochastic stylematch

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:44:07.372061Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T22:44:07.011458Z digest=sha256:8f187d2cd7f2da30efaae29bd9062135a4962ce1b7e7b0ed04434e89354e211e

Pith citing papers

No inbound Pith citation observations are available.