CAT: Class Aware Adaptive Thresholding for Semi-Supervised Domain Generalization | Paper Citation Record

Observation 828fd144-dcc5-4821-93c9-caebe6cd2934 · outbound

This paper cites Adaptive consistency regular- ization for semi-supervised transfer learning.

CAT: Class Aware Adaptive Thresholding for Semi-Supervised Domain Generalization Adaptive consistency regular- ization for semi-supervised transfer learning

Reference 1

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Observation 64f4c72f-ea67-4139-bdac-f21110b008aa · outbound

This paper cites Self-training: A survey.

CAT: Class Aware Adaptive Thresholding for Semi-Supervised Domain Generalization Self-training: A survey

Reference 2

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Observation 39adb4cb-3520-440a-88af-9806b1e438d1 · outbound

This paper cites Learn- ing with pseudo-ensembles.

CAT: Class Aware Adaptive Thresholding for Semi-Supervised Domain Generalization Learn- ing with pseudo-ensembles

Reference 3

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Observation 92179f40-f122-4c52-aa40-3cb68b97a91b · outbound

This paper cites Metareg: Towards domain generalization using meta- regularization.

CAT: Class Aware Adaptive Thresholding for Semi-Supervised Domain Generalization Metareg: Towards domain generalization using meta- regularization

Reference 4

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Observation e29cfd96-299f-479a-b408-1ed0c992a119 · outbound

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

CAT: Class Aware Adaptive Thresholding for Semi-Supervised Domain Generalization Mixmatch: A holistic approach to semi-supervised learning

Reference 5

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Observation 8406f2da-8c2e-43e4-a602-6f890dd520cb · outbound

This paper cites AdaMatch: A Unified Approach to Semi-Supervised Learning and Domain Adaptation.

CAT: Class Aware Adaptive Thresholding for Semi-Supervised Domain Generalization AdaMatch: A Unified Approach to Semi-Supervised Learning and Domain Adaptation

Reference 6

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Observation aedd9225-95e9-4cc5-8c96-54b929d8297e · outbound

This paper cites Curriculum labeling: Revisiting pseudo-labeling for semi-supervised learning.

CAT: Class Aware Adaptive Thresholding for Semi-Supervised Domain Generalization Curriculum labeling: Revisiting pseudo-labeling for semi-supervised learning

Reference 7

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Observation 20890600-b586-4fa8-95c1-973ec03f8b16 · outbound

This paper cites Domain generalization by mutual-information regu- larization with pre-trained models.

CAT: Class Aware Adaptive Thresholding for Semi-Supervised Domain Generalization Domain generalization by mutual-information regu- larization with pre-trained models

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:48:50.620567Z

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Observation 4aca3534-3e97-4ffe-80f9-38a4943d2321 · outbound

This paper cites Debiased self-training for semi-supervised learning.

CAT: Class Aware Adaptive Thresholding for Semi-Supervised Domain Generalization Debiased self-training for semi-supervised learning

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:48:50.602273Z

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Observation cc702479-10d0-49e2-9662-eed1550ff963 · outbound

This paper cites Self-training avoids using spurious features under domain shift.

CAT: Class Aware Adaptive Thresholding for Semi-Supervised Domain Generalization Self-training avoids using spurious features under domain shift

Reference 10

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Observation 5dec8873-a25e-433d-9cc1-a2145a74dffe · outbound

This paper cites Randaugment: Practical automated data augmen- tation with a reduced search space.

CAT: Class Aware Adaptive Thresholding for Semi-Supervised Domain Generalization Randaugment: Practical automated data augmen- tation with a reduced search space

Reference 11

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Observation 6655cb23-f5d3-4756-99d6-75f98a3316f5 · outbound

This paper cites Deep domain generalization with structured low-rank constraint.

CAT: Class Aware Adaptive Thresholding for Semi-Supervised Domain Generalization Deep domain generalization with structured low-rank constraint

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:48:50.545094Z

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Observation cbe054e5-5b35-4707-807b-95dc52d8766f · outbound

This paper cites Domain gener- alization with domain-specific aggregation modules.

CAT: Class Aware Adaptive Thresholding for Semi-Supervised Domain Generalization Domain gener- alization with domain-specific aggregation modules

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:48:50.524812Z

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Observation 43d568de-1a2a-4eb4-be34-fb4eac77ded5 · outbound

This paper cites Domain-adversarial training of neural networks.

CAT: Class Aware Adaptive Thresholding for Semi-Supervised Domain Generalization Domain-adversarial training of neural networks

Reference 14

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Observation bd1569a7-0458-4fb5-b07c-5d7e07ec1f77 · outbound

This paper cites Unsupervised Representation Learning by Predicting Image Rotations.

CAT: Class Aware Adaptive Thresholding for Semi-Supervised Domain Generalization Unsupervised Representation Learning by Predicting Image Rotations

Reference 15

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Observation 25fb23fe-65dc-417a-9dec-3207bdd123c6 · outbound

This paper cites Semi-supervised learning by entropy minimization.

CAT: Class Aware Adaptive Thresholding for Semi-Supervised Domain Generalization Semi-supervised learning by entropy minimization

Reference 16

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Observation 90082c6a-44a1-4d35-ace9-7f5be435ee35 · outbound

This paper cites Class-imbalanced semi- supervised learning with adaptive thresholding.

CAT: Class Aware Adaptive Thresholding for Semi-Supervised Domain Generalization Class-imbalanced semi- supervised learning with adaptive thresholding

Reference 17

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Observation cc26e991-af64-4070-aedd-f5454150b06d · outbound

This paper cites Semi-supervised learning.

CAT: Class Aware Adaptive Thresholding for Semi-Supervised Domain Generalization Semi-supervised learning

Reference 18

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Observation 7db7cd7e-b79c-47c9-949c-e8b2a127b473 · outbound

This paper cites Deep residual learning for image recognition.

CAT: Class Aware Adaptive Thresholding for Semi-Supervised Domain Generalization Deep residual learning for image recognition

Reference 19

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Observation 8168eb07-8ed4-497c-9f9e-45690e056066 · outbound

This paper cites Self-challenging improves cross-domain generalization.

CAT: Class Aware Adaptive Thresholding for Semi-Supervised Domain Generalization Self-challenging improves cross-domain generalization

Reference 20

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Observation f847dc2c-ef76-4450-b697-124b6d919134 · outbound

This paper cites Domain- guided weight modulation for semi-supervised domain gen- eralization.

CAT: Class Aware Adaptive Thresholding for Semi-Supervised Domain Generalization Domain- guided weight modulation for semi-supervised domain gen- eralization

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:48:50.410861Z

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Observation 2e9a24d7-69a9-41d1-baf8-3fefecc21065 · outbound

This paper cites Dual student: Breaking the limits of the teacher in semi-supervised learning.

CAT: Class Aware Adaptive Thresholding for Semi-Supervised Domain Generalization Dual student: Breaking the limits of the teacher in semi-supervised learning

Reference 22

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Observation b72ef058-c37d-407e-9bd0-33c0ab957718 · outbound

This paper cites Supervised contrastive learning.

CAT: Class Aware Adaptive Thresholding for Semi-Supervised Domain Generalization Supervised contrastive learning

Reference 23

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Observation 891d4e0f-f0ed-493b-b9d1-3104cbda6bd3 · outbound

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

CAT: Class Aware Adaptive Thresholding for Semi-Supervised Domain Generalization Selfreg: Self-supervised contrastive regu- larization for domain generalization

Reference 24

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Observation 8a67269e-6e15-4049-95ad-1e969b9a33c0 · outbound

This paper cites Semi-supervised learning.

CAT: Class Aware Adaptive Thresholding for Semi-Supervised Domain Generalization Semi-supervised learning

Reference 25

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Observation f4b85f0d-f4d5-4e92-89c7-4a46a00bbd3d · outbound

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

CAT: Class Aware Adaptive Thresholding for Semi-Supervised Domain Generalization Pseudo-label: The simple and effi- cient semi-supervised learning method for deep neural net- works

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:48:50.330934Z

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation a7cc3438-4083-49dc-820a-08de942e0d27 · outbound

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

CAT: Class Aware Adaptive Thresholding for Semi-Supervised Domain Generalization Deeper, broader and artier domain generaliza- tion

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:48:50.310952Z

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Observation 10e90489-7882-4153-9e9f-3854e20ffcff · outbound

This paper cites Domain generalization for med- ical imaging classification with linear-dependency regular- ization.

CAT: Class Aware Adaptive Thresholding for Semi-Supervised Domain Generalization Domain generalization for med- ical imaging classification with linear-dependency regular- ization

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:48:50.294420Z

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Observation a23b1289-ae5d-45b5-bcb2-4975e4b6519a · outbound

This paper cites Selective-supervised contrastive learning with noisy labels.

CAT: Class Aware Adaptive Thresholding for Semi-Supervised Domain Generalization Selective-supervised contrastive learning with noisy labels

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:48:50.278161Z

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Observation 8a3ae0fd-b80f-4b14-8638-2529e1570709 · outbound

This paper cites Domain generalization via conditional invari- ant representations.

CAT: Class Aware Adaptive Thresholding for Semi-Supervised Domain Generalization Domain generalization via conditional invari- ant representations

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:48:50.260430Z

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Observation 6998bb78-812e-45c2-a7e8-f636b7449e3f · outbound

This paper cites Feature-critic networks for heterogeneous do- main generalization.

CAT: Class Aware Adaptive Thresholding for Semi-Supervised Domain Generalization Feature-critic networks for heterogeneous do- main generalization

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:48:50.234642Z

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Observation 7907acf5-32be-4550-b475-a512f40c36d4 · outbound

This paper cites Smooth neighbors on teacher graphs for semi-supervised learning.

CAT: Class Aware Adaptive Thresholding for Semi-Supervised Domain Generalization Smooth neighbors on teacher graphs for semi-supervised learning

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:48:50.215283Z

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Observation 10e7ceb9-f1a8-4e82-bbdd-7544d46940f2 · outbound

This paper cites Towards recognizing unseen categories in un- seen domains.

CAT: Class Aware Adaptive Thresholding for Semi-Supervised Domain Generalization Towards recognizing unseen categories in un- seen domains

Reference 33

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Observation 3a5be908-a061-4567-bfc3-28802c41a9dd · outbound

This paper cites Robust place categorization with deep do- main generalization.

CAT: Class Aware Adaptive Thresholding for Semi-Supervised Domain Generalization Robust place categorization with deep do- main generalization

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:48:50.164545Z

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 4df13c88-6b4a-446f-8a14-1384f7a1c517 · outbound

This paper cites Domain generalization via invariant fea- ture representation.

CAT: Class Aware Adaptive Thresholding for Semi-Supervised Domain Generalization Domain generalization via invariant fea- ture representation

Reference 35

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Observation 28bf8d5e-6927-48e7-ae3e-46ef86517173 · outbound

This paper cites Unsupervised learning of visual representations by solving jigsaw puzzles.

CAT: Class Aware Adaptive Thresholding for Semi-Supervised Domain Generalization Unsupervised learning of visual representations by solving jigsaw puzzles

Reference 36

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Observation 341312eb-1cc4-4652-b4a7-b9c95e1abff1 · outbound

This paper cites Multi-objective interpolation train- ing for robustness to label noise.

CAT: Class Aware Adaptive Thresholding for Semi-Supervised Domain Generalization Multi-objective interpolation train- ing for robustness to label noise

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:48:50.100758Z

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Observation afb725ee-8148-49ec-b595-f1915576cc8f · outbound

This paper cites Mul- timatch: Multi-task learning for semi-supervised domain generalization.

CAT: Class Aware Adaptive Thresholding for Semi-Supervised Domain Generalization Mul- timatch: Multi-task learning for semi-supervised domain generalization

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:48:50.076522Z

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Observation 1abb6269-966a-4b0a-863f-a37c370bce9a · outbound

This paper cites Learning to optimize domain specific normalization for domain generalization.

CAT: Class Aware Adaptive Thresholding for Semi-Supervised Domain Generalization Learning to optimize domain specific normalization for domain generalization

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:48:50.051881Z

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Observation f4732ef3-5141-42f5-8e31-dd75e8a220b9 · outbound

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

CAT: Class Aware Adaptive Thresholding for Semi-Supervised Domain Generalization Generalizing Across Domains via Cross-Gradient Training

Reference 40

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Observation 1e90df95-861d-4a82-a3ad-af520497c2b3 · outbound

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

CAT: Class Aware Adaptive Thresholding for Semi-Supervised Domain Generalization Fixmatch: Simplifying semi-supervised learning with consistency and confidence

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:48:50.027294Z

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation ec0a211f-9904-483f-8d39-680cdddae1aa · outbound

This paper cites Measuring domain shift for deep learning in histopathology.

CAT: Class Aware Adaptive Thresholding for Semi-Supervised Domain Generalization Measuring domain shift for deep learning in histopathology

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:48:50.010750Z

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 0117791c-52da-4e03-9560-532627fb5a5a · outbound

This paper cites Sinkhorn label allocation: Semi-supervised classification via annealed self-training.

CAT: Class Aware Adaptive Thresholding for Semi-Supervised Domain Generalization Sinkhorn label allocation: Semi-supervised classification via annealed self-training

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:48:49.992055Z

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Observation 6127ed79-1b4e-4089-a7de-fdcce5ab26aa · outbound

This paper cites Mean teachers are better role models: Weight-averaged consistency targets improve semi-supervised deep learning results.

CAT: Class Aware Adaptive Thresholding for Semi-Supervised Domain Generalization Mean teachers are better role models: Weight-averaged consistency targets improve semi-supervised deep learning results

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:48:49.971769Z

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 66a16e1d-69bb-455c-b7c9-a5f77fc16c6a · outbound

This paper cites Inter- polation consistency training for semi-supervised learning.

CAT: Class Aware Adaptive Thresholding for Semi-Supervised Domain Generalization Inter- polation consistency training for semi-supervised learning

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:48:49.943045Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 93ad11ae-b203-4590-ac24-c79ca612afd7 · outbound

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

CAT: Class Aware Adaptive Thresholding for Semi-Supervised Domain Generalization Generalizing to unseen domains: A survey on do- main generalization

Reference 46

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Observation eb31a839-2e79-46af-8b06-6a1cdf9f7cc1 · outbound

This paper cites Learning from extrinsic and intrinsic su- pervisions for domain generalization.

CAT: Class Aware Adaptive Thresholding for Semi-Supervised Domain Generalization Learning from extrinsic and intrinsic su- pervisions for domain generalization

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:48:49.905129Z

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Observation edcb2053-7ae3-4361-aa94-c3c4433c2509 · outbound

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

CAT: Class Aware Adaptive Thresholding for Semi-Supervised Domain Generalization FreeMatch: Self-adaptive Thresholding for Semi-supervised Learning

Reference 48

Resolution: unresolved; no resolver link, observed 2026-08-11T17:48:49.107104Z

Source-reported events for the cited work

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Observation 72b20638-525d-409a-9253-9fba0fa8d8aa · outbound

This paper cites Crest: A class-rebalancing self-training frame- work for imbalanced semi-supervised learning.

CAT: Class Aware Adaptive Thresholding for Semi-Supervised Domain Generalization Crest: A class-rebalancing self-training frame- work for imbalanced semi-supervised learning

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:48:49.886609Z

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Observation 3e79b0ca-af3a-425a-9de9-0c7d84d6e2f0 · outbound

This paper cites Unsupervised data augmentation for consistency training.

CAT: Class Aware Adaptive Thresholding for Semi-Supervised Domain Generalization Unsupervised data augmentation for consistency training

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:48:49.870683Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation ee439041-cecb-4576-a0af-17d818e8fb87 · outbound

This paper cites Dash: Semi-supervised learning with dynamic thresholding.

CAT: Class Aware Adaptive Thresholding for Semi-Supervised Domain Generalization Dash: Semi-supervised learning with dynamic thresholding

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:48:49.852237Z

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Observation 4359cfce-c17a-4014-84f5-88d810bf37f8 · outbound

This paper cites Robust and Generalizable Visual Representation Learning via Random Convolutions.

CAT: Class Aware Adaptive Thresholding for Semi-Supervised Domain Generalization Robust and Generalizable Visual Representation Learning via Random Convolutions

Reference 52

Resolution: unresolved; no resolver link, observed 2026-08-11T17:48:49.260701Z

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Observation e3f3dea6-b203-4ad8-bec1-f97c36c4a972 · outbound

This paper cites A survey on deep semi-supervised learning.

CAT: Class Aware Adaptive Thresholding for Semi-Supervised Domain Generalization A survey on deep semi-supervised learning

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:48:49.832972Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 6be81d23-2236-4d63-9f37-3068d490434e · outbound

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

CAT: Class Aware Adaptive Thresholding for Semi-Supervised Domain Generalization Pcl: Proxy-based contrastive learning for domain generalization

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:48:49.814838Z

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This paper cites Semi-supervised domain generalization with known and unknown classes.

CAT: Class Aware Adaptive Thresholding for Semi-Supervised Domain Generalization Semi-supervised domain generalization with known and unknown classes

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:48:49.798994Z

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Observation de37a347-28c7-41e4-b93a-fbe9d0f6eb27 · outbound

This paper cites Adaptive risk min- imization: Learning to adapt to domain shift.

CAT: Class Aware Adaptive Thresholding for Semi-Supervised Domain Generalization Adaptive risk min- imization: Learning to adapt to domain shift

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:48:49.781468Z

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 50fbc737-382f-4bec-af4b-7897d8d830e9 · outbound

This paper cites Lassl: Label-guided self-training for semi- supervised learning.

CAT: Class Aware Adaptive Thresholding for Semi-Supervised Domain Generalization Lassl: Label-guided self-training for semi- supervised learning

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:48:49.763527Z

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Observation 562cdde5-3f9d-443a-8f27-58276b853bd2 · outbound

This paper cites Domain generalization: A survey.

CAT: Class Aware Adaptive Thresholding for Semi-Supervised Domain Generalization Domain generalization: A survey

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:48:49.745919Z

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Observation a0fe3ad1-39dc-43af-93e5-15a7ab1e97b3 · outbound

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

CAT: Class Aware Adaptive Thresholding for Semi-Supervised Domain Generalization Semi-supervised domain generalization with stochastic stylematch

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:48:49.727250Z

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Observation c5a6787c-a0ed-49e5-a620-db2b96ba69f0 · outbound

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

CAT: Class Aware Adaptive Thresholding for Semi-Supervised Domain Generalization Deep domain-adversarial image generation for do- main generalisation

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:48:49.708809Z

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Observation 1989e117-3b3e-4f75-8bbd-28c2709713dc · outbound

This paper cites Domain Generalization with MixStyle.

CAT: Class Aware Adaptive Thresholding for Semi-Supervised Domain Generalization Domain Generalization with MixStyle

Reference 61

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Observation bc7444d6-9906-45f2-b4e8-c30b55385d03 · outbound

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

CAT: Class Aware Adaptive Thresholding for Semi-Supervised Domain Generalization Mixstyle neural networks for domain generalization and adaptation

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:48:49.690264Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation b15c2071-f712-4873-b705-1f7692a8b204 · outbound

This paper cites Introduction to semi- supervised learning.

CAT: Class Aware Adaptive Thresholding for Semi-Supervised Domain Generalization Introduction to semi- supervised learning

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:48:49.669358Z

Source-reported events for the cited work

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