Post-Training Augmentation Invariance | Paper Citation Record

Observation 1ba0c117-450f-4641-8d6c-175e0b6427b5 · outbound

This paper cites Gradient flows: in metric spaces and in the space of probability measures.

Post-Training Augmentation Invariance Gradient flows: in metric spaces and in the space of probability measures

Reference 1

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Observation d36a9c88-86ed-4c8a-86b8-e26aa25564c7 · outbound

This paper cites Wasserstein generative adversarial networks.

Post-Training Augmentation Invariance Wasserstein generative adversarial networks

Reference 2

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Observation cad896cf-5fb8-4bfe-93aa-bb6abdc774ad · outbound

This paper cites Learning representations by maximizing mutual information across views.

Post-Training Augmentation Invariance Learning representations by maximizing mutual information across views

Reference 3

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Observation aeb1f28b-6fdb-4cdd-9585-02714249d56d · outbound

This paper cites Wasserstein distributional robustness of neural networks.

Post-Training Augmentation Invariance Wasserstein distributional robustness of neural networks

Reference 4

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Observation 55db2047-6098-4fe4-8e14-de3fccfef464 · outbound

This paper cites Mutual information neural estimation.

Post-Training Augmentation Invariance Mutual information neural estimation

Reference 5

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Observation 33048c72-f9ab-4a2f-bc16-c3592ed2cd54 · outbound

This paper cites Lower bounds on adversarial robustness from optimal transport.

Post-Training Augmentation Invariance Lower bounds on adversarial robustness from optimal transport

Reference 6

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Observation 23ce7926-b0a8-46a4-9863-4ea022a4a307 · outbound

This paper cites Measure theory, volume 1.

Post-Training Augmentation Invariance Measure theory, volume 1

Reference 7

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Observation 7ba3d9db-dc77-49b0-91e7-955adc0b1fd6 · outbound

This paper cites Sliced and radon wasserstein barycenters of measures.

Post-Training Augmentation Invariance Sliced and radon wasserstein barycenters of measures

Reference 8

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Observation e85547c8-6782-435e-96b8-43cfdeb7b4b9 · outbound

This paper cites Unidimensional and evolution methods for optimal transportation.

Post-Training Augmentation Invariance Unidimensional and evolution methods for optimal transportation

Reference 9

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Observation 92e2cc34-07af-4089-8a1f-9fcaf4c0bb97 · outbound

This paper cites From optimal transport to generative modeling: the VEGAN cookbook.

Post-Training Augmentation Invariance From optimal transport to generative modeling: the VEGAN cookbook

Reference 10

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Observation ffd2c8a0-87c1-4077-ad9d-d5e57b9ab889 · outbound

This paper cites Unsupervised learning of visual features by contrasting cluster assignments.

Post-Training Augmentation Invariance Unsupervised learning of visual features by contrasting cluster assignments

Reference 11

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Observation 6a856c58-6952-4906-9cac-9584ffb490c3 · outbound

This paper cites Emerging properties in self-supervised vision transformers.

Post-Training Augmentation Invariance Emerging properties in self-supervised vision transformers

Reference 12

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Observation d42060e0-d727-446e-85c3-a72f2575638c · outbound

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

Post-Training Augmentation Invariance A simple framework for contrastive learning of visual representations

Reference 13

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Observation ab2e1ef6-8695-47de-833b-5c55f72db48c · outbound

This paper cites Disintegration and bayesian inversion via string diagrams.

Post-Training Augmentation Invariance Disintegration and bayesian inversion via string diagrams

Reference 14

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Observation f5e68ab6-6b7b-4943-adaf-3da99943259e · outbound

This paper cites Pointless learning.

Post-Training Augmentation Invariance Pointless learning

Reference 15

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Observation 8c7dcfb5-2240-42f8-b785-28163ba0f84c · outbound

This paper cites Optimal transport for domain adaptation.

Post-Training Augmentation Invariance Optimal transport for domain adaptation

Reference 16

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Observation c52d6b1b-5795-4d62-b970-254b11bacbf2 · outbound

This paper cites Joint distribution optimal transportation for domain adaptation.

Post-Training Augmentation Invariance Joint distribution optimal transportation for domain adaptation

Reference 17

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Observation b9baa01c-feeb-43c8-8e8b-bb464acccedd · outbound

This paper cites A categorical foundation for bayesian probability.

Post-Training Augmentation Invariance A categorical foundation for bayesian probability

Reference 18

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Observation 2ddfbb83-9cd0-404b-b34c-35251cd80852 · outbound

This paper cites Sinkhorn distances: Lightspeed computation of optimal transport.

Post-Training Augmentation Invariance Sinkhorn distances: Lightspeed computation of optimal transport

Reference 19

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Observation 8ff6fae6-2283-4072-a327-8de96e1fc5c5 · outbound

This paper cites An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale.

Post-Training Augmentation Invariance An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Reference 20

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Observation 2f6e9459-d646-40d9-ac7c-224239391fe2 · outbound

This paper cites Your representations are in the network: composable and parallel adaptation for large scale models.

Post-Training Augmentation Invariance Your representations are in the network: composable and parallel adaptation for large scale models

Reference 21

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Observation f3cf3810-3369-4bef-b966-c65f77494f9a · outbound

This paper cites Bayesian Inference for Markov Kernels Valued in Wasserstein Spaces.

Post-Training Augmentation Invariance Bayesian Inference for Markov Kernels Valued in Wasserstein Spaces

Reference 22

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Observation 3a4c5c03-676e-42e6-b8b3-ed208b974817 · outbound

This paper cites A synthetic approach to markov kernels, conditional independence and theorems on sufficient statistics.

Post-Training Augmentation Invariance A synthetic approach to markov kernels, conditional independence and theorems on sufficient statistics

Reference 23

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Observation 2c261036-3ab8-442e-9c80-7590954f2711 · outbound

This paper cites Finetune like you pretrain: Improved finetuning of zero-shot vision models.

Post-Training Augmentation Invariance Finetune like you pretrain: Improved finetuning of zero-shot vision models

Reference 24

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Observation fde4a796-dc15-4177-aadf-4b5dd13c4433 · outbound

This paper cites Measuring statistical dependence with hilbert-schmidt norms.

Post-Training Augmentation Invariance Measuring statistical dependence with hilbert-schmidt norms

Reference 25

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Observation 9bd3519f-11b3-4da6-8938-9d535b3a1455 · outbound

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

Post-Training Augmentation Invariance Bootstrap your own latent-a new approach to self-supervised learning

Reference 26

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Observation ebcf8775-72d2-48ff-865f-a97d63e59229 · outbound

This paper cites Momentum contrast for unsupervised visual representation learning.

Post-Training Augmentation Invariance Momentum contrast for unsupervised visual representation learning

Reference 27

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Observation f5abc7bb-5a2a-46e6-929d-83289a934f95 · outbound

This paper cites Masked autoencoders are scalable vision learners.

Post-Training Augmentation Invariance Masked autoencoders are scalable vision learners

Reference 28

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Observation e97c7b66-6fda-4596-b35f-548bc1e14ca8 · outbound

This paper cites Learning deep representations by mutual information estimation and maximization.

Post-Training Augmentation Invariance Learning deep representations by mutual information estimation and maximization

Reference 29

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Observation 36a47224-b1db-4c51-a916-3cb0b9b9ad8c · outbound

This paper cites Learning discrete representations via information maximizing self-augmented training.

Post-Training Augmentation Invariance Learning discrete representations via information maximizing self-augmented training

Reference 30

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Observation 6cceaea9-a0d0-4600-972d-479d9f9cada3 · outbound

This paper cites Customizing domain adapters for domain generalization.

Post-Training Augmentation Invariance Customizing domain adapters for domain generalization

Reference 31

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Observation 78676e12-acaa-4344-92de-f45c080f032d · outbound

This paper cites Foundations of Modern Probability.

Post-Training Augmentation Invariance Foundations of Modern Probability

Reference 32

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Observation 78817684-4e51-4c07-927d-eeb89871bc85 · outbound

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

Post-Training Augmentation Invariance Selfreg: Self-supervised contrastive regularization for domain generalization

Reference 33

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Observation 601d606d-46fa-4d12-acac-ce0a6261cdc0 · outbound

This paper cites Sliced wasserstein auto-encoders.

Post-Training Augmentation Invariance Sliced wasserstein auto-encoders

Reference 34

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Observation 8e766a37-027b-4690-9878-aaef7d9e4984 · outbound

This paper cites Fine-Tuning can Distort Pretrained Features and Underperform Out-of-Distribution.

Post-Training Augmentation Invariance Fine-Tuning can Distort Pretrained Features and Underperform Out-of-Distribution

Reference 35

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Observation 71edce8a-8d7a-483a-aa42-c9764efc8e69 · outbound

This paper cites A Wasserstein perspective of Vanilla GANs.

Post-Training Augmentation Invariance A Wasserstein perspective of Vanilla GANs

Reference 36

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Observation af4a1c83-d588-4ec8-8345-2edb08b822b9 · outbound

This paper cites Sliced wasserstein discrepancy for unsupervised domain adaptation.

Post-Training Augmentation Invariance Sliced wasserstein discrepancy for unsupervised domain adaptation

Reference 37

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Observation 1c1d0aeb-5207-4aaa-ad7e-cafe4a625acc · outbound

This paper cites Wasserstein smoothing: Certified robustness against wasserstein adversarial attacks.

Post-Training Augmentation Invariance Wasserstein smoothing: Certified robustness against wasserstein adversarial attacks

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:55:34.146421Z

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Observation 73f550df-f949-40b2-b302-f5e209b5cee3 · outbound

This paper cites an unresolved cited work.

Post-Training Augmentation Invariance Unresolved cited work

Reference 39

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Observation f6614d7f-e500-4f3f-89a4-72ec1d6cc321 · outbound

This paper cites Self-supervised learning with kernel dependence maximization.

Post-Training Augmentation Invariance Self-supervised learning with kernel dependence maximization

Reference 40

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Observation b9e6824c-6bc0-4aa8-96c0-606f91fb87a2 · outbound

This paper cites Self-organization in a perceptual network.

Post-Training Augmentation Invariance Self-organization in a perceptual network

Reference 41

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Observation 37602075-946b-4f19-a759-e9f2b59c5448 · outbound

This paper cites Entropy regularized optimal transport independence criterion.

Post-Training Augmentation Invariance Entropy regularized optimal transport independence criterion

Reference 42

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Observation 0cf1ed3a-f9b8-4ea1-a4c2-af281496866c · outbound

This paper cites Sliced-wasserstein flows: Nonparametric generative modeling via optimal transport and diffusions.

Post-Training Augmentation Invariance Sliced-wasserstein flows: Nonparametric generative modeling via optimal transport and diffusions

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:55:34.097179Z

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Observation b0eebd88-c2b9-44fb-a157-3543994a4453 · outbound

This paper cites Decoupled Weight Decay Regularization.

Post-Training Augmentation Invariance Decoupled Weight Decay Regularization

Reference 44

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Observation 5ce2fd77-ca85-49bb-9550-440843b20a34 · outbound

This paper cites Formal limitations on the measurement of mutual information.

Post-Training Augmentation Invariance Formal limitations on the measurement of mutual information

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:55:34.086472Z

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Observation d68f092e-59c8-4c4d-9f86-8b2658f2a507 · outbound

This paper cites Measuring dependence between random vectors via optimal transport.

Post-Training Augmentation Invariance Measuring dependence between random vectors via optimal transport

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:55:34.075311Z

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Observation 82f71de8-a1f8-4295-9c0e-6d51a82913b5 · outbound

This paper cites The Earth Mover's Correlation.

Post-Training Augmentation Invariance The Earth Mover's Correlation

Reference 47

Resolution: unresolved; no resolver link, observed 2026-08-15T20:55:33.631178Z

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Observation 09524049-0930-4685-9d89-4450a1bc38e2 · outbound

This paper cites Asymptotic guarantees for learning generative models with the sliced-wasserstein distance.

Post-Training Augmentation Invariance Asymptotic guarantees for learning generative models with the sliced-wasserstein distance

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:55:34.064624Z

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Observation 6f851820-bbbf-4228-80d3-ea4314918327 · outbound

This paper cites Hierarchical Sliced Wasserstein Distance.

Post-Training Augmentation Invariance Hierarchical Sliced Wasserstein Distance

Reference 49

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Observation 93040b96-195b-4dfb-8b38-f030168ffab6 · outbound

This paper cites Optimal transport model distributional robustness.

Post-Training Augmentation Invariance Optimal transport model distributional robustness

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:55:34.053684Z

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Observation c2d3b3dd-0648-4cba-bdc3-28b4b727ac54 · outbound

This paper cites Transport Dependency: Optimal Transport Based Dependency Measures.

Post-Training Augmentation Invariance Transport Dependency: Optimal Transport Based Dependency Measures

Reference 51

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Observation 8f720718-3e10-4637-add4-4c632844a596 · outbound

This paper cites Representation Learning with Contrastive Predictive Coding.

Post-Training Augmentation Invariance Representation Learning with Contrastive Predictive Coding

Reference 52

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Observation 480a1976-4997-497f-8abf-58dbab91cbff · outbound

This paper cites DINOv2: Learning Robust Visual Features without Supervision.

Post-Training Augmentation Invariance DINOv2: Learning Robust Visual Features without Supervision

Reference 53

Resolution: unresolved; no resolver link, observed 2026-08-15T20:55:33.651640Z

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Observation 5069a6be-64a2-45a1-bf45-923573d5acbe · outbound

This paper cites Wasserstein dependency measure for representation learning.

Post-Training Augmentation Invariance Wasserstein dependency measure for representation learning

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:55:34.042312Z

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Observation fb6d3ff1-3ba5-450a-b35c-a52a3ead624b · outbound

This paper cites Hausdorff and wasserstein metrics on graphs and other structured data.

Post-Training Augmentation Invariance Hausdorff and wasserstein metrics on graphs and other structured data

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:55:34.032081Z

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Observation 522ea27b-c6e8-46a2-aec8-43aa2c0003f0 · outbound

This paper cites On variational bounds of mutual information.

Post-Training Augmentation Invariance On variational bounds of mutual information

Reference 56

Resolution: unresolved; no resolver link, observed 2026-08-15T20:55:33.661196Z

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Observation 07e20b74-6f2f-431b-b3e8-70a276a0b5de · outbound

This paper cites Mass Transportation Problems: Volume 1: Theory.

Post-Training Augmentation Invariance Mass Transportation Problems: Volume 1: Theory

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:55:34.016607Z

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Observation 24439f6d-1bd9-402e-9677-11a392b5cd2a · outbound

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

Post-Training Augmentation Invariance Learning transferable visual models from natural language supervision

Reference 58

Resolution: unresolved; no resolver link, observed 2026-08-15T20:55:33.668349Z

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Observation bb575514-7f52-4544-827e-c902472a32ea · outbound

This paper cites Learning multiple visual domains with residual adapters.

Post-Training Augmentation Invariance Learning multiple visual domains with residual adapters

Reference 59

Resolution: unresolved; no resolver link, observed 2026-08-15T20:55:33.672301Z

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Observation 156aff44-88e6-4806-9f67-74668553b292 · outbound

This paper cites Learning representations by maximizing mutual information in variational autoencoders.

Post-Training Augmentation Invariance Learning representations by maximizing mutual information in variational autoencoders

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:55:33.994388Z

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Observation aac9c08c-90bb-4ca8-be68-aef2564fefc7 · outbound

This paper cites Kornia: an open source differentiable computer vision library for pytorch.

Post-Training Augmentation Invariance Kornia: an open source differentiable computer vision library for pytorch

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:55:33.982906Z

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Observation d4a8d7ed-2d94-414c-8e0a-f1033c84d4f0 · outbound

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

Post-Training Augmentation Invariance Wasserstein distance guided representation learning for domain adaptation

Reference 62

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Observation d2c37623-6f1f-487b-ad1b-ba8c5d49f8fe · outbound

This paper cites Wasserstein Auto-Encoders.

Post-Training Augmentation Invariance Wasserstein Auto-Encoders

Reference 63

Resolution: unresolved; no resolver link, observed 2026-08-15T20:55:33.685298Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3926993d-bd33-45de-bcc6-f3367c220122 · outbound

This paper cites On Mutual Information Maximization for Representation Learning.

Post-Training Augmentation Invariance On Mutual Information Maximization for Representation Learning

Reference 64

Resolution: unresolved; no resolver link, observed 2026-08-15T20:55:33.688735Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 750c9778-cfb5-4acf-9796-cfe32bee8c2d · outbound

This paper cites Topics in Optimal Transportation.

Post-Training Augmentation Invariance Topics in Optimal Transportation

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:55:33.966454Z

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Observation 426bdde7-d26a-440e-ac5e-c7a9667fe01a · outbound

This paper cites an unresolved cited work.

Post-Training Augmentation Invariance Unresolved cited work

Reference 66

Resolution: unresolved; raw_fallback, observed 2026-08-15T20:55:33.955670Z

Source-reported events for the cited work

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

Observation 66f84c7e-a5b2-4989-b4d5-3b41b75e90bd · outbound

This paper cites Wasserstein adversarial examples via projected sinkhorn iterations.

Post-Training Augmentation Invariance Wasserstein adversarial examples via projected sinkhorn iterations

Reference 67

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:55:33.946086Z

Source-reported events for the cited work

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

Observation fcdee3d3-90b1-40d7-ac59-b855c3bbb875 · outbound

This paper cites Robust fine-tuning of zero-shot models.

Post-Training Augmentation Invariance Robust fine-tuning of zero-shot models

Reference 68

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:55:33.935480Z

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Observation 08ac99dd-aa75-48f1-85cd-31b409f4b857 · outbound

This paper cites Sliced wasserstein generative models.

Post-Training Augmentation Invariance Sliced wasserstein generative models

Reference 69

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:55:33.924118Z

Source-reported events for the cited work

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

Observation 70b0a922-8eda-4b0e-a844-392e40284a50 · outbound

This paper cites Stronger and faster wasserstein adversarial attacks.

Post-Training Augmentation Invariance Stronger and faster wasserstein adversarial attacks

Reference 70

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:55:33.914520Z

Source-reported events for the cited work

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Observation 00b0e212-80f1-4c66-81cb-7effd847717d · outbound

This paper cites Disentangled Representation Learning with Wasserstein Total Correlation.

Post-Training Augmentation Invariance Disentangled Representation Learning with Wasserstein Total Correlation

Reference 71

Resolution: unresolved; no resolver link, observed 2026-08-15T20:55:33.713090Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d38d7d9b-6351-4ec6-bd60-9336df122e3d · outbound

This paper cites Parameter-efficient fine-tuning for pre-trained vision models: A survey.

Post-Training Augmentation Invariance Parameter-efficient fine-tuning for pre-trained vision models: A survey

Reference 72

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:55:33.904781Z

Source-reported events for the cited work

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

Observation 100fa268-89d9-4e9f-b2fa-a0cb5d693c3d · outbound

This paper cites Side adapter network for open-vocabulary semantic segmentation.

Post-Training Augmentation Invariance Side adapter network for open-vocabulary semantic segmentation

Reference 73

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:55:33.895175Z

Source-reported events for the cited work

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

Observation e5422ee8-479d-4422-88ba-f868d0836e06 · outbound

This paper cites Infovae: Balancing learning and inference in variational autoencoders.

Post-Training Augmentation Invariance Infovae: Balancing learning and inference in variational autoencoders

Reference 74

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:55:33.885778Z

Source-reported events for the cited work

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

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