Source-free Semantic Regularization Learning for Semi-supervised Domain Adaptation | Paper Citation Record

Observation b234cfd5-9025-47ca-9c28-dd19c5a1c669 · outbound

This paper cites Imagenet classification with deep convolutional neural networks,.

Source-free Semantic Regularization Learning for Semi-supervised Domain Adaptation Imagenet classification with deep convolutional neural networks,

Reference 1

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Observation 402747e6-faeb-4c2f-8a40-de535429fecf · outbound

This paper cites Deep residual learning for image recognition,.

Source-free Semantic Regularization Learning for Semi-supervised Domain Adaptation Deep residual learning for image recognition,

Reference 2

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Observation 58ae10d8-a742-4f11-9de1-c5358b5b4d68 · outbound

This paper cites Xnor-net: Imagenet classification using binary convolutional neural networks,.

Source-free Semantic Regularization Learning for Semi-supervised Domain Adaptation Xnor-net: Imagenet classification using binary convolutional neural networks,

Reference 3

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Observation 4ceac889-84df-4cf2-8ff2-698d1ef9f966 · outbound

This paper cites Imagenet classification with deep convolutional neural networks,.

Source-free Semantic Regularization Learning for Semi-supervised Domain Adaptation Imagenet classification with deep convolutional neural networks,

Reference 4

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Observation 7465569c-0519-47fa-8f7a-f4e07f1a991d · outbound

This paper cites Transductive episodic-wise adaptive metric for few-shot learning,.

Source-free Semantic Regularization Learning for Semi-supervised Domain Adaptation Transductive episodic-wise adaptive metric for few-shot learning,

Reference 5

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Observation 9a79b501-916f-419b-8938-fd1bf27111ea · outbound

This paper cites Image classification by cross-media active learning with privileged information,.

Source-free Semantic Regularization Learning for Semi-supervised Domain Adaptation Image classification by cross-media active learning with privileged information,

Reference 6

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Observation 819a5918-0a93-4c60-a430-0bc2ad6e0ff1 · outbound

This paper cites Csps: An adaptive pooling method for image classification,.

Source-free Semantic Regularization Learning for Semi-supervised Domain Adaptation Csps: An adaptive pooling method for image classification,

Reference 7

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Observation 9141555c-7f3a-4dcd-8153-a3375d015125 · outbound

This paper cites Fully convolutional networks for semantic segmentation,.

Source-free Semantic Regularization Learning for Semi-supervised Domain Adaptation Fully convolutional networks for semantic segmentation,

Reference 8

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Observation 28a2023f-908e-42ca-95cf-27cbc4a752b9 · outbound

This paper cites Fbsnet: A fast bilateral symmetrical network for real-time semantic segmentation,.

Source-free Semantic Regularization Learning for Semi-supervised Domain Adaptation Fbsnet: A fast bilateral symmetrical network for real-time semantic segmentation,

Reference 9

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Observation 05c98496-e121-4226-bc5c-f2d145650adf · outbound

This paper cites Semantic segmentation guided pixel fusion for image retargeting,.

Source-free Semantic Regularization Learning for Semi-supervised Domain Adaptation Semantic segmentation guided pixel fusion for image retargeting,

Reference 10

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Observation 9c7842bb-d823-450a-9eb1-dd616707f45d · outbound

This paper cites Image segmentation using deep learning: A survey,.

Source-free Semantic Regularization Learning for Semi-supervised Domain Adaptation Image segmentation using deep learning: A survey,

Reference 11

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Observation d1a3cbf1-fee1-4f9e-9a00-ed9739fe636b · outbound

This paper cites Muva: A new large-scale benchmark for multi-view amodal instance segmentation in the shopping scenario,.

Source-free Semantic Regularization Learning for Semi-supervised Domain Adaptation Muva: A new large-scale benchmark for multi-view amodal instance segmentation in the shopping scenario,

Reference 12

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Observation 6620b10c-f8fe-4e0f-a466-22c741d278bd · outbound

This paper cites SegGPT: Segmenting Everything In Context.

Source-free Semantic Regularization Learning for Semi-supervised Domain Adaptation SegGPT: Segmenting Everything In Context

Reference 13

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Observation 4c6afac2-3f83-4c01-8102-4c412b251948 · outbound

This paper cites Domain adaptation via transfer component analysis,.

Source-free Semantic Regularization Learning for Semi-supervised Domain Adaptation Domain adaptation via transfer component analysis,

Reference 14

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Observation b968e54b-9e71-4c20-8891-a9b13377ca19 · outbound

This paper cites Visual domain adaptation: A survey of recent advances,.

Source-free Semantic Regularization Learning for Semi-supervised Domain Adaptation Visual domain adaptation: A survey of recent advances,

Reference 15

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Observation c36e8f0f-96ce-4011-9f93-015585e33957 · outbound

This paper cites Instance adaptive self-training for unsupervised domain adaptation,.

Source-free Semantic Regularization Learning for Semi-supervised Domain Adaptation Instance adaptive self-training for unsupervised domain adaptation,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:40:30.413048Z

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Observation 27ac41f3-80d6-405e-97c8-2f4283137595 · outbound

This paper cites Self-guided adaptation: Progressive representation alignment for do- main adaptive object detection,.

Source-free Semantic Regularization Learning for Semi-supervised Domain Adaptation Self-guided adaptation: Progressive representation alignment for do- main adaptive object detection,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:40:30.402512Z

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Observation 10c22d0b-7117-49ab-b36d-349d7f7eb1b0 · outbound

This paper cites Unsupervised domain adaptation by backpropagation,.

Source-free Semantic Regularization Learning for Semi-supervised Domain Adaptation Unsupervised domain adaptation by backpropagation,

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-10T22:40:29.323021Z

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Observation a44824c4-2b55-4cf5-9ebe-9ed192ad5d2e · outbound

This paper cites Informative feature disentanglement for unsupervised do- main adaptation,.

Source-free Semantic Regularization Learning for Semi-supervised Domain Adaptation Informative feature disentanglement for unsupervised do- main adaptation,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:40:30.386722Z

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Observation 930adb19-b3ff-4017-b23e-9dffa7fd23b9 · outbound

This paper cites Cross- domain contrastive learning for unsupervised domain adaptation,.

Source-free Semantic Regularization Learning for Semi-supervised Domain Adaptation Cross- domain contrastive learning for unsupervised domain adaptation,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:40:30.376095Z

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Observation 70bb9df7-26db-4e29-8528-5f96e18bacfd · outbound

This paper cites Adversarial mixup ratio confusion for unsupervised domain adaptation,.

Source-free Semantic Regularization Learning for Semi-supervised Domain Adaptation Adversarial mixup ratio confusion for unsupervised domain adaptation,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:40:30.365444Z

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Observation 83969694-58c2-415a-9d63-b6c5749fb444 · outbound

This paper cites Discriminative invariant alignment for unsupervised domain adaptation,.

Source-free Semantic Regularization Learning for Semi-supervised Domain Adaptation Discriminative invariant alignment for unsupervised domain adaptation,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:40:30.354585Z

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Observation 586b4e76-926a-4cee-bc13-23d0893b446b · outbound

This paper cites A review of single-source deep unsupervised visual domain adaptation,.

Source-free Semantic Regularization Learning for Semi-supervised Domain Adaptation A review of single-source deep unsupervised visual domain adaptation,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:40:30.343888Z

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Observation 4c490fd0-ffc7-4380-966c-23a55df7d0ff · outbound

This paper cites Dual structural knowledge interaction for domain adaptation,.

Source-free Semantic Regularization Learning for Semi-supervised Domain Adaptation Dual structural knowledge interaction for domain adaptation,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:40:30.333650Z

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Observation f46d77bf-660c-40a8-b7c9-af1db31da082 · outbound

This paper cites Unsupervised domain adaptation via risk-consistent estimators,.

Source-free Semantic Regularization Learning for Semi-supervised Domain Adaptation Unsupervised domain adaptation via risk-consistent estimators,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:40:30.323909Z

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Observation 5b640fec-d738-4695-a9d0-c9cab3d19e71 · outbound

This paper cites Semi- supervised domain adaptation via minimax entropy,.

Source-free Semantic Regularization Learning for Semi-supervised Domain Adaptation Semi- supervised domain adaptation via minimax entropy,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:40:30.314593Z

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Observation 35173e74-bbb5-4888-801d-637a0984b7b0 · outbound

This paper cites Cross-domain adaptive clustering for semi-supervised domain adaptation,.

Source-free Semantic Regularization Learning for Semi-supervised Domain Adaptation Cross-domain adaptive clustering for semi-supervised domain adaptation,

Reference 27

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Observation 058cfe51-36d1-41b7-9aba-eedafa278420 · outbound

This paper cites Ecacl: A holistic framework for semi-supervised domain adaptation,.

Source-free Semantic Regularization Learning for Semi-supervised Domain Adaptation Ecacl: A holistic framework for semi-supervised domain adaptation,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:40:30.293608Z

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Observation fa5f0d00-6e48-4b66-a353-0e5f6d5129d1 · outbound

This paper cites Semi- supervised domain adaptive structure learning,.

Source-free Semantic Regularization Learning for Semi-supervised Domain Adaptation Semi- supervised domain adaptive structure learning,

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:40:30.283620Z

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Observation 02402209-177d-4be5-a9d3-c8251f9d2642 · outbound

This paper cites Semi-supervised semantic seg- mentation with prototype-based consistency regularization,.

Source-free Semantic Regularization Learning for Semi-supervised Domain Adaptation Semi-supervised semantic seg- mentation with prototype-based consistency regularization,

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:40:30.273461Z

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Observation 0ed8bd06-9535-4d4a-9d1e-a39b6a422081 · outbound

This paper cites Multi-level Consistency Learning for Semi-supervised Domain Adaptation.

Source-free Semantic Regularization Learning for Semi-supervised Domain Adaptation Multi-level Consistency Learning for Semi-supervised Domain Adaptation

Reference 31

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Observation 9ea5479e-de40-478f-86b5-b8d03fcd41e4 · outbound

This paper cites Semi-supervised domain adaptation with source label adaptation,.

Source-free Semantic Regularization Learning for Semi-supervised Domain Adaptation Semi-supervised domain adaptation with source label adaptation,

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:40:30.261277Z

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Observation 8e80da7b-0f38-448f-be21-feb65e437e45 · outbound

This paper cites Semi-supervised Domain Adaptation via Prototype-based Multi-level Learning.

Source-free Semantic Regularization Learning for Semi-supervised Domain Adaptation Semi-supervised Domain Adaptation via Prototype-based Multi-level Learning

Reference 33

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Observation 9268a6f5-dec1-4863-ad7e-8638a20d9584 · outbound

This paper cites Adaptive betweenness clustering for semi- supervised domain adaptation,.

Source-free Semantic Regularization Learning for Semi-supervised Domain Adaptation Adaptive betweenness clustering for semi- supervised domain adaptation,

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:40:30.250838Z

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Observation cad3020f-0214-43ce-b40e-5b5fa849cf5e · outbound

This paper cites Inter-domain mixup for semi-supervised domain adaptation,.

Source-free Semantic Regularization Learning for Semi-supervised Domain Adaptation Inter-domain mixup for semi-supervised domain adaptation,

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:40:30.238594Z

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Observation 01f1444c-250f-4b58-a4ae-c8bbc028314a · outbound

This paper cites Semi-supervised domain adaptation for major depressive disorder detection,.

Source-free Semantic Regularization Learning for Semi-supervised Domain Adaptation Semi-supervised domain adaptation for major depressive disorder detection,

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:40:30.227064Z

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Observation 22949bd6-19e4-47de-9b20-0696672a91c4 · outbound

This paper cites Attract, perturb, and explore: Learning a feature alignment network for semi-supervised domain adaptation,.

Source-free Semantic Regularization Learning for Semi-supervised Domain Adaptation Attract, perturb, and explore: Learning a feature alignment network for semi-supervised domain adaptation,

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:40:30.216280Z

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Observation b0c11168-6788-415a-a0ad-0e0c32b1208f · outbound

This paper cites Do we really need to access the source data? source hypothesis transfer for unsupervised domain adaptation,.

Source-free Semantic Regularization Learning for Semi-supervised Domain Adaptation Do we really need to access the source data? source hypothesis transfer for unsupervised domain adaptation,

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:40:30.205148Z

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Observation ae93ad68-b2cb-42c9-ab67-c7e3b3bed810 · outbound

This paper cites Hard negative examples are hard, but useful,.

Source-free Semantic Regularization Learning for Semi-supervised Domain Adaptation Hard negative examples are hard, but useful,

Reference 39

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Observation ec5d29bf-3588-4266-a848-bb3946683a3c · outbound

This paper cites Challenging tough samples in unsupervised domain adaptation,.

Source-free Semantic Regularization Learning for Semi-supervised Domain Adaptation Challenging tough samples in unsupervised domain adaptation,

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:40:30.181566Z

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Observation d8bdd5fb-f6bc-4bc8-9499-364a138c09e6 · outbound

This paper cites Complementary attention-driven contrastive learning with hard-sample exploring for unsupervised do- main adaptive person re-id,.

Source-free Semantic Regularization Learning for Semi-supervised Domain Adaptation Complementary attention-driven contrastive learning with hard-sample exploring for unsupervised do- main adaptive person re-id,

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:40:30.169876Z

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Observation 9e5aeade-b9fd-4149-b0cb-fca354c439a4 · outbound

This paper cites Confidence- based visual dispersal for few-shot unsupervised domain adaptation,.

Source-free Semantic Regularization Learning for Semi-supervised Domain Adaptation Confidence- based visual dispersal for few-shot unsupervised domain adaptation,

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:40:30.157194Z

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Observation 310a176a-7b21-4af0-9834-203578f0a5f2 · outbound

This paper cites mixup: Beyond Empirical Risk Minimization.

Source-free Semantic Regularization Learning for Semi-supervised Domain Adaptation mixup: Beyond Empirical Risk Minimization

Reference 43

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Observation dae2a2e8-e3b0-4f53-a76c-d90067281d54 · outbound

This paper cites Early- learning regularization prevents memorization of noisy labels,.

Source-free Semantic Regularization Learning for Semi-supervised Domain Adaptation Early- learning regularization prevents memorization of noisy labels,

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:40:30.145929Z

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Observation 7a96f661-3335-4421-978d-2af2b76c8903 · outbound

This paper cites When Source-Free Domain Adaptation Meets Learning with Noisy Labels.

Source-free Semantic Regularization Learning for Semi-supervised Domain Adaptation When Source-Free Domain Adaptation Meets Learning with Noisy Labels

Reference 45

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Observation b0efbcd1-114b-4fb2-be37-8ecfbfd3d74d · outbound

This paper cites Multi-adversarial domain adaptation,.

Source-free Semantic Regularization Learning for Semi-supervised Domain Adaptation Multi-adversarial domain adaptation,

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:40:30.135941Z

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Observation 91e97ffd-df6f-49db-a207-26351ca416b9 · outbound

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

Source-free Semantic Regularization Learning for Semi-supervised Domain Adaptation Deep hashing network for unsupervised domain adaptation,

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:40:30.125717Z

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Observation 8a6411f7-d749-490d-9a05-09f557eb191d · outbound

This paper cites Adapting visual cate- gory models to new domains,.

Source-free Semantic Regularization Learning for Semi-supervised Domain Adaptation Adapting visual cate- gory models to new domains,

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:40:30.114493Z

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Observation 55beb6c6-df8c-4044-9680-46344d912036 · outbound

This paper cites A kernel two-sample test,.

Source-free Semantic Regularization Learning for Semi-supervised Domain Adaptation A kernel two-sample test,

Reference 49

Resolution: unresolved; no resolver link, observed 2026-08-10T22:40:29.431066Z

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Observation a9067900-3433-4035-8029-e1aaeedc6ab0 · outbound

This paper cites Domain-adversarial training of neural networks,.

Source-free Semantic Regularization Learning for Semi-supervised Domain Adaptation Domain-adversarial training of neural networks,

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:40:30.096835Z

Source-reported events for the cited work

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Observation 9a6ef81e-0044-4950-8538-71daa17bdf14 · outbound

This paper cites Deep transfer learning with joint adaptation networks,.

Source-free Semantic Regularization Learning for Semi-supervised Domain Adaptation Deep transfer learning with joint adaptation networks,

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:40:30.085482Z

Source-reported events for the cited work

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Observation 861b7ccf-694f-4a35-a48b-37fe81aa8bda · outbound

This paper cites Correlation alignment for unsupervised domain adaptation,.

Source-free Semantic Regularization Learning for Semi-supervised Domain Adaptation Correlation alignment for unsupervised domain adaptation,

Reference 52

Resolution: unresolved; no resolver link, observed 2026-08-10T22:40:29.441102Z

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Observation 6b7f555d-1fad-4664-ab69-cfbe48e9a51e · outbound

This paper cites Deep unsupervised convolutional domain adaptation,.

Source-free Semantic Regularization Learning for Semi-supervised Domain Adaptation Deep unsupervised convolutional domain adaptation,

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:40:30.069172Z

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Observation bf2b33a5-7b20-4e88-bda9-71c45529afff · outbound

This paper cites Adversarial discrim- inative domain adaptation,.

Source-free Semantic Regularization Learning for Semi-supervised Domain Adaptation Adversarial discrim- inative domain adaptation,

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:40:30.058657Z

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Observation 43efa091-6a38-44ff-aacd-2af80d31bef6 · outbound

This paper cites Joint distribution alignment via adversarial learning for domain adaptive object detection,.

Source-free Semantic Regularization Learning for Semi-supervised Domain Adaptation Joint distribution alignment via adversarial learning for domain adaptive object detection,

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:40:30.048645Z

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Observation d20f389c-b6b6-4509-be88-c9982723c666 · outbound

This paper cites Learning semantic representa- tions for unsupervised domain adaptation,.

Source-free Semantic Regularization Learning for Semi-supervised Domain Adaptation Learning semantic representa- tions for unsupervised domain adaptation,

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:40:30.037329Z

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation fc95b847-ea19-487d-a3d7-2e07f3f3c309 · outbound

This paper cites Wasserstein distance guided representation learning for domain adaptation,.

Source-free Semantic Regularization Learning for Semi-supervised Domain Adaptation Wasserstein distance guided representation learning for domain adaptation,

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:40:30.026413Z

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 1c330ed7-48f1-4bbd-816f-2ec1a1f329d6 · outbound

This paper cites Unsupervised domain adap- tation via deep conditional adaptation network,.

Source-free Semantic Regularization Learning for Semi-supervised Domain Adaptation Unsupervised domain adap- tation via deep conditional adaptation network,

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:40:30.016129Z

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation fa2f5d13-396d-4e65-aede-9acacf60045e · outbound

This paper cites Adversarial network with multiple classifiers for open set domain adaptation,.

Source-free Semantic Regularization Learning for Semi-supervised Domain Adaptation Adversarial network with multiple classifiers for open set domain adaptation,

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:40:30.005038Z

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation b357b1a2-8556-4f22-ac47-6a5f9b3d7baa · outbound

This paper cites Progressive feature alignment for unsupervised domain adaptation,.

Source-free Semantic Regularization Learning for Semi-supervised Domain Adaptation Progressive feature alignment for unsupervised domain adaptation,

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:40:29.995372Z

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 9f10e7d3-ed76-4546-a3eb-36b9cac8ed4e · outbound

This paper cites Transferrable prototypical networks for unsupervised domain adaptation,.

Source-free Semantic Regularization Learning for Semi-supervised Domain Adaptation Transferrable prototypical networks for unsupervised domain adaptation,

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:40:29.985339Z

Source-reported events for the cited work

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Observation 4ddf43b4-e9ff-4961-8285-6b271352a6f2 · outbound

This paper cites How does the combined risk affect the performance of unsupervised domain adaptation approaches?,.

Source-free Semantic Regularization Learning for Semi-supervised Domain Adaptation How does the combined risk affect the performance of unsupervised domain adaptation approaches?,

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:40:29.975680Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 6f3b39c6-d1fa-4d22-b22d-ba0ba85774e4 · outbound

This paper cites Improving semi-supervised domain adaptation using effective target selection and semantics,.

Source-free Semantic Regularization Learning for Semi-supervised Domain Adaptation Improving semi-supervised domain adaptation using effective target selection and semantics,

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:40:29.965057Z

Source-reported events for the cited work

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Observation 25a9f5b1-7729-4660-a558-15c584bf9396 · outbound

This paper cites Deep co-training with task decomposition for semi-supervised domain adaptation,.

Source-free Semantic Regularization Learning for Semi-supervised Domain Adaptation Deep co-training with task decomposition for semi-supervised domain adaptation,

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:40:29.954367Z

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 5ac8a03a-df05-42c9-8180-cc5b0e64b96b · outbound

This paper cites Contradictory structure learning for semi-supervised domain adaptation,.

Source-free Semantic Regularization Learning for Semi-supervised Domain Adaptation Contradictory structure learning for semi-supervised domain adaptation,

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:40:29.942799Z

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 8b7bb2b6-5735-4b27-b308-a4740f1016bb · outbound

This paper cites Bidirectional adversarial training for semi-supervised domain adaptation.,.

Source-free Semantic Regularization Learning for Semi-supervised Domain Adaptation Bidirectional adversarial training for semi-supervised domain adaptation.,

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:40:29.929468Z

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 72f4c278-d26f-4b0e-a936-b4d90f6b3513 · outbound

This paper cites Context-guided entropy minimization for semi-supervised domain adaptation,.

Source-free Semantic Regularization Learning for Semi-supervised Domain Adaptation Context-guided entropy minimization for semi-supervised domain adaptation,

Reference 67

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:40:29.917128Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation de75f2e0-c148-4955-a281-738675809127 · outbound

This paper cites Representation Learning with Contrastive Predictive Coding.

Source-free Semantic Regularization Learning for Semi-supervised Domain Adaptation Representation Learning with Contrastive Predictive Coding

Reference 68

Resolution: unresolved; no resolver link, observed 2026-08-10T22:40:29.494354Z

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Observation 70150ee4-3e19-4504-80a5-0a61f881d6d1 · outbound

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

Source-free Semantic Regularization Learning for Semi-supervised Domain Adaptation Bootstrap your own latent-a new approach to self-supervised learning,

Reference 69

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:40:29.904656Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation a0a54f78-616f-4fa2-acb7-318a068d960c · outbound

This paper cites Supervised contrastive learn- ing,.

Source-free Semantic Regularization Learning for Semi-supervised Domain Adaptation Supervised contrastive learn- ing,

Reference 70

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:40:29.893793Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 6a2ad74c-f2a7-48cd-b15c-f2c792b9c8be · outbound

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

Source-free Semantic Regularization Learning for Semi-supervised Domain Adaptation A simple framework for contrastive learning of visual representations,

Reference 71

Resolution: unresolved; no resolver link, observed 2026-08-10T22:40:29.504522Z

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Observation 40b13301-e947-4dcb-a35f-699b00896424 · outbound

This paper cites Probabilistic Contrastive Learning for Domain Adaptation.

Source-free Semantic Regularization Learning for Semi-supervised Domain Adaptation Probabilistic Contrastive Learning for Domain Adaptation

Reference 72

Resolution: unresolved; no resolver link, observed 2026-08-10T22:40:29.507641Z

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Observation 7550ad98-a8cd-44ee-8592-2f8a0477e260 · outbound

This paper cites Heterogeneous contrastive learning: Encoding spa- tial information for compact visual representations,.

Source-free Semantic Regularization Learning for Semi-supervised Domain Adaptation Heterogeneous contrastive learning: Encoding spa- tial information for compact visual representations,

Reference 73

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:40:29.876622Z

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Observation 19fc4a20-3335-4ceb-997c-752178f65adf · outbound

This paper cites Semi-supervised contrastive learning with similarity co-calibration,.

Source-free Semantic Regularization Learning for Semi-supervised Domain Adaptation Semi-supervised contrastive learning with similarity co-calibration,

Reference 74

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:40:29.865904Z

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Observation d5a6283b-7848-4938-85c5-90b598c1f804 · outbound

This paper cites Learning from different samples: A source-free framework for semi-supervised domain adapta- tion,.

Source-free Semantic Regularization Learning for Semi-supervised Domain Adaptation Learning from different samples: A source-free framework for semi-supervised domain adapta- tion,

Reference 75

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:40:29.855391Z

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Observation 0d84dc78-73c3-49c3-9d53-4810e6dd2d69 · outbound

This paper cites Class-aware contrastive semi-supervised learn- ing,.

Source-free Semantic Regularization Learning for Semi-supervised Domain Adaptation Class-aware contrastive semi-supervised learn- ing,

Reference 76

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:40:29.844180Z

Source-reported events for the cited work

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Observation df503c99-e947-4ae0-93c6-59b2b5c822f3 · outbound

This paper cites Momentum contrast for unsupervised visual representation learning,.

Source-free Semantic Regularization Learning for Semi-supervised Domain Adaptation Momentum contrast for unsupervised visual representation learning,

Reference 77

Resolution: unresolved; no resolver link, observed 2026-08-10T22:40:29.525040Z

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Observation 386693c4-b804-4af0-ab3d-ee91b27b0467 · outbound

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

Source-free Semantic Regularization Learning for Semi-supervised Domain Adaptation Mixmatch: A holistic approach to semi-supervised learning,

Reference 78

Resolution: unresolved; no resolver link, observed 2026-08-10T22:40:29.528297Z

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Observation 47253364-d809-474f-8621-6fbd4efdaa8a · outbound

This paper cites How Does Mixup Help With Robustness and Generalization?.

Source-free Semantic Regularization Learning for Semi-supervised Domain Adaptation How Does Mixup Help With Robustness and Generalization?

Reference 79

Resolution: unresolved; no resolver link, observed 2026-08-10T22:40:29.531976Z

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Observation c23f0ce6-5c33-40d7-b357-d9ce782217af · outbound

This paper cites On mixup regu- larization,.

Source-free Semantic Regularization Learning for Semi-supervised Domain Adaptation On mixup regu- larization,

Reference 80

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:40:29.821459Z

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Observation 9f00bab5-0026-4a65-a656-b01e42b70000 · outbound

This paper cites Prevalence of neural collapse during the terminal phase of deep learning training,.

Source-free Semantic Regularization Learning for Semi-supervised Domain Adaptation Prevalence of neural collapse during the terminal phase of deep learning training,

Reference 81

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:40:29.810487Z

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Observation 0148e3c1-df96-453e-9d78-469e253af7ae · outbound

This paper cites Proxymix: Proxy-based mixup training with label refinery for source-free domain adaptation,.

Source-free Semantic Regularization Learning for Semi-supervised Domain Adaptation Proxymix: Proxy-based mixup training with label refinery for source-free domain adaptation,

Reference 82

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:40:29.800133Z

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Observation 8e26f24a-b10c-4247-8fcc-1a8af627efa1 · outbound

This paper cites Understanding and improving early stopping for learning with noisy labels,.

Source-free Semantic Regularization Learning for Semi-supervised Domain Adaptation Understanding and improving early stopping for learning with noisy labels,

Reference 83

Resolution: unresolved; no resolver link, observed 2026-08-10T22:40:29.546558Z

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Observation 4a6738f2-09cf-4cdd-9fbd-f0f077cf546d · outbound

This paper cites Prestopping: How does early stopping help generalization against label noise?,.

Source-free Semantic Regularization Learning for Semi-supervised Domain Adaptation Prestopping: How does early stopping help generalization against label noise?,

Reference 84

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:40:29.784139Z

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Observation ea813e69-76f9-490e-943f-1c6254415981 · outbound

This paper cites Semi-supervised learning by entropy minimization,.

Source-free Semantic Regularization Learning for Semi-supervised Domain Adaptation Semi-supervised learning by entropy minimization,

Reference 85

Resolution: unresolved; no resolver link, observed 2026-08-10T22:40:29.553471Z

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Observation e96495de-f1d6-44d3-87ba-65135c848109 · outbound

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

Source-free Semantic Regularization Learning for Semi-supervised Domain Adaptation Clda: Contrastive learning for semi-supervised domain adaptation,

Reference 86

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:40:29.767169Z

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Observation 333de6d8-ed52-483f-8077-922cef123c59 · outbound

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

Source-free Semantic Regularization Learning for Semi-supervised Domain Adaptation Moment matching for multi-source domain adaptation,

Reference 87

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:40:29.756201Z

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 56f99d04-f601-41a0-8e31-4e0da451c695 · outbound

This paper cites Very Deep Convolutional Networks for Large-Scale Image Recognition.

Source-free Semantic Regularization Learning for Semi-supervised Domain Adaptation Very Deep Convolutional Networks for Large-Scale Image Recognition

Reference 88

Resolution: unresolved; no resolver link, observed 2026-08-10T22:40:29.564068Z

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Observation ad772a01-aa92-49c2-9f3c-1299a256f331 · outbound

This paper cites Randaugment: Practical automated data augmentation with a reduced search space,.

Source-free Semantic Regularization Learning for Semi-supervised Domain Adaptation Randaugment: Practical automated data augmentation with a reduced search space,

Reference 89

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:40:29.745704Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 7f2350c1-9bf0-4b8b-a7cc-6a184ad1963c · outbound

This paper cites Pytorch: An imperative style, high-performance deep learning library,.

Source-free Semantic Regularization Learning for Semi-supervised Domain Adaptation Pytorch: An imperative style, high-performance deep learning library,

Reference 90

Resolution: unresolved; no resolver link, observed 2026-08-10T22:40:29.570754Z

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Observation 9cee15e0-6495-43e8-b26e-c9ae01fba68a · outbound

This paper cites Visualizing data using t-sne.,.

Source-free Semantic Regularization Learning for Semi-supervised Domain Adaptation Visualizing data using t-sne.,

Reference 91

Resolution: unresolved; no resolver link, observed 2026-08-10T22:40:29.574910Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ccd2f70c-2bfc-4a53-9c6d-1f9d523738d2 · outbound

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

Source-free Semantic Regularization Learning for Semi-supervised Domain Adaptation Grad-cam: Visual explanations from deep networks via gradient-based localization,

Reference 92

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:40:29.721164Z

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation a47d62b9-150f-4eeb-b114-2f22b84380db · outbound

This paper cites Transferability vs. dis- criminability: Batch spectral penalization for adversarial domain adap- tation,.

Source-free Semantic Regularization Learning for Semi-supervised Domain Adaptation Transferability vs. dis- criminability: Batch spectral penalization for adversarial domain adap- tation,

Reference 93

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:40:29.710482Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation d0c6a3f9-0faa-48af-985c-ed66fb1d8d44 · outbound

This paper cites A collaborative alignment framework of transferable knowledge extraction for unsuper- vised domain adaptation,.

Source-free Semantic Regularization Learning for Semi-supervised Domain Adaptation A collaborative alignment framework of transferable knowledge extraction for unsuper- vised domain adaptation,

Reference 94

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:40:29.699050Z

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