Improving Knowledge Distillation Under Unknown Covariate Shift Through Confidence-Guided Data Augmentation | Paper Citation Record

Observation 34c47bba-2875-40d5-9d92-92d31bb1228e · outbound

This paper cites Fairness Without Demographic Data: A Survey of Approaches.

Improving Knowledge Distillation Under Unknown Covariate Shift Through Confidence-Guided Data Augmentation Fairness Without Demographic Data: A Survey of Approaches

Reference 1

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Observation a7529d71-6eff-45dd-a63d-30003c497670 · outbound

This paper cites DASH: Detection and Assessment of Systematic Hallucinations of VLMs.

Improving Knowledge Distillation Under Unknown Covariate Shift Through Confidence-Guided Data Augmentation DASH: Detection and Assessment of Systematic Hallucinations of VLMs

Reference 2

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This paper cites DiG-IN: Diffusion Guidance for Investigating Networks - Uncovering Classifier Differences, Neuron Visualisations, and Visual Counterfactual Explanations.

Improving Knowledge Distillation Under Unknown Covariate Shift Through Confidence-Guided Data Augmentation DiG-IN: Diffusion Guidance for Investigating Networks - Uncovering Classifier Differences, Neuron Visualisations, and Visual Counterfactual Explanations

Reference 3

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Observation e8c0a85b-523a-4642-8983-1375e0ce1046 · outbound

This paper cites Synthetic Data from Diffusion Models Improves ImageNet Classification.

Improving Knowledge Distillation Under Unknown Covariate Shift Through Confidence-Guided Data Augmentation Synthetic Data from Diffusion Models Improves ImageNet Classification

Reference 4

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Observation 18fce0e1-818a-4d20-b601-a3866da28271 · outbound

This paper cites Knowledge distillation: A good teacher is patient and consistent.

Improving Knowledge Distillation Under Unknown Covariate Shift Through Confidence-Guided Data Augmentation Knowledge distillation: A good teacher is patient and consistent

Reference 5

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Observation 7aa5a15d-22f3-4e3c-a882-5287c028640e · outbound

This paper cites AutoAug- ment: Learning Augmentation Strategies From Data.

Improving Knowledge Distillation Under Unknown Covariate Shift Through Confidence-Guided Data Augmentation AutoAug- ment: Learning Augmentation Strategies From Data

Reference 6

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Observation 127db8e1-665f-457b-84a2-ca27f8d3019c · outbound

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

Improving Knowledge Distillation Under Unknown Covariate Shift Through Confidence-Guided Data Augmentation An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Reference 7

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Observation a7e42a6d-aaa8-42e2-ade7-76d935b889a7 · outbound

This paper cites DataComp: In search of the next generation of multimodal datasets.

Improving Knowledge Distillation Under Unknown Covariate Shift Through Confidence-Guided Data Augmentation DataComp: In search of the next generation of multimodal datasets

Reference 8

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Observation 3b1d5473-b755-4f6c-8d83-eb64bcf5c025 · outbound

This paper cites Shortcut learning in deep neural networks.

Improving Knowledge Distillation Under Unknown Covariate Shift Through Confidence-Guided Data Augmentation Shortcut learning in deep neural networks

Reference 9

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Observation 24893922-7104-44e7-8580-c4e28dfe3567 · outbound

This paper cites ASPIRE: Language-Guided Data Augmentation for Improving Robustness Against Spurious Correlations.

Improving Knowledge Distillation Under Unknown Covariate Shift Through Confidence-Guided Data Augmentation ASPIRE: Language-Guided Data Augmentation for Improving Robustness Against Spurious Correlations

Reference 10

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Observation 115ba8a3-89cc-4a69-b916-27b2010b9ead · outbound

This paper cites Knowledge Distillation: A Survey.

Improving Knowledge Distillation Under Unknown Covariate Shift Through Confidence-Guided Data Augmentation Knowledge Distillation: A Survey

Reference 11

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Observation ee523e8e-1566-4ded-8b7a-fc86654ec574 · outbound

This paper cites Revisit the Power of Vanilla Knowledge Distillation: from Small Scale to Large Scale.

Improving Knowledge Distillation Under Unknown Covariate Shift Through Confidence-Guided Data Augmentation Revisit the Power of Vanilla Knowledge Distillation: from Small Scale to Large Scale

Reference 12

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Observation 22279265-9780-4bc1-a1ff-3ce924113a9c · outbound

This paper cites Distilling the Knowledge in a Neural Network.

Improving Knowledge Distillation Under Unknown Covariate Shift Through Confidence-Guided Data Augmentation Distilling the Knowledge in a Neural Network

Reference 13

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This paper cites Active Generation for Image Classification.

Improving Knowledge Distillation Under Unknown Covariate Shift Through Confidence-Guided Data Augmentation Active Generation for Image Classification

Reference 14

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This paper cites Version 0.1.

Improving Knowledge Distillation Under Unknown Covariate Shift Through Confidence-Guided Data Augmentation Version 0.1

Reference 15

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This paper cites Challenges and Opportunities in Improving Worst-Group Generalization in Presence of Spurious Features.

Improving Knowledge Distillation Under Unknown Covariate Shift Through Confidence-Guided Data Augmentation Challenges and Opportunities in Improving Worst-Group Generalization in Presence of Spurious Features

Reference 16

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Observation 67784cdf-51ae-47b6-bbac-41003a511102 · outbound

This paper cites Last Layer Re-Training is Sufficient for Robustness to Spurious Correlations.

Improving Knowledge Distillation Under Unknown Covariate Shift Through Confidence-Guided Data Augmentation Last Layer Re-Training is Sufficient for Robustness to Spurious Correlations

Reference 17

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Observation 115f45ed-b455-4d55-9250-35f6c626f579 · outbound

This paper cites Towards Last-layer Retraining for Group Robustness with Fewer Annotations.

Improving Knowledge Distillation Under Unknown Covariate Shift Through Confidence-Guided Data Augmentation Towards Last-layer Retraining for Group Robustness with Fewer Annotations

Reference 18

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Observation 7361fdb4-8d0e-4e3e-9eac-3f8419178602 · outbound

This paper cites BigDatasetGAN: Synthesizing ImageNet with Pixel-wise Annotations.

Improving Knowledge Distillation Under Unknown Covariate Shift Through Confidence-Guided Data Augmentation BigDatasetGAN: Synthesizing ImageNet with Pixel-wise Annotations

Reference 19

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Observation 8fb82dbc-2545-4a94-8837-f7eb2451acf2 · outbound

This paper cites Adversarial Supervision Makes Layout-to-Image Diffusion Models Thrive.

Improving Knowledge Distillation Under Unknown Covariate Shift Through Confidence-Guided Data Augmentation Adversarial Supervision Makes Layout-to-Image Diffusion Models Thrive

Reference 20

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Observation ba81d721-7590-4ae5-acf8-a677a847622f · outbound

This paper cites The Genetic Overlap Between Hair and Eye Color.

Improving Knowledge Distillation Under Unknown Covariate Shift Through Confidence-Guided Data Augmentation The Genetic Overlap Between Hair and Eye Color

Reference 21

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This paper cites Just Train Twice: Improving Group Robustness without Training Group Information.

Improving Knowledge Distillation Under Unknown Covariate Shift Through Confidence-Guided Data Augmentation Just Train Twice: Improving Group Robustness without Training Group Information

Reference 22

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This paper cites Deep Learning Face Attributes in the Wild.

Improving Knowledge Distillation Under Unknown Covariate Shift Through Confidence-Guided Data Augmentation Deep Learning Face Attributes in the Wild

Reference 23

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Observation 4b0ff37b-61e8-46bf-a5f1-ff676c9034b1 · outbound

This paper cites Decoupled Weight Decay Regularization.

Improving Knowledge Distillation Under Unknown Covariate Shift Through Confidence-Guided Data Augmentation Decoupled Weight Decay Regularization

Reference 24

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This paper cites A Comprehensive Survey on Knowledge Distilla- tion.

Improving Knowledge Distillation Under Unknown Covariate Shift Through Confidence-Guided Data Augmentation A Comprehensive Survey on Knowledge Distilla- tion

Reference 25

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Observation 196105c2-f1a2-4347-9fe4-beb2616e3256 · outbound

This paper cites AWADA: Attention-Weighted Adversarial Domain Adaptation for Object Detection.

Improving Knowledge Distillation Under Unknown Covariate Shift Through Confidence-Guided Data Augmentation AWADA: Attention-Weighted Adversarial Domain Adaptation for Object Detection

Reference 26

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Observation 00d53fcc-2f01-4887-ad60-fea7cf8bfd96 · outbound

This paper cites A statistical perspective on distillation.

Improving Knowledge Distillation Under Unknown Covariate Shift Through Confidence-Guided Data Augmentation A statistical perspective on distillation

Reference 27

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Observation dd0b9fec-3a54-4a84-bf44-efcde022769e · outbound

This paper cites Null-text Inversion for Editing Real Images using Guided Diffusion Models.

Improving Knowledge Distillation Under Unknown Covariate Shift Through Confidence-Guided Data Augmentation Null-text Inversion for Editing Real Images using Guided Diffusion Models

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:35:25.529646Z

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This paper cites Spurious Features Everywhere - Large-Scale Detection of Harmful Spurious Features in ImageNet.

Improving Knowledge Distillation Under Unknown Covariate Shift Through Confidence-Guided Data Augmentation Spurious Features Everywhere - Large-Scale Detection of Harmful Spurious Features in ImageNet

Reference 29

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This paper cites BEiT v2: Masked Image Modeling with Vector-Quantized Visual Tokenizers.

Improving Knowledge Distillation Under Unknown Covariate Shift Through Confidence-Guided Data Augmentation BEiT v2: Masked Image Modeling with Vector-Quantized Visual Tokenizers

Reference 30

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This paper cites Towards Understanding Knowledge Distillation.

Improving Knowledge Distillation Under Unknown Covariate Shift Through Confidence-Guided Data Augmentation Towards Understanding Knowledge Distillation

Reference 31

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This paper cites Feature Distillation Improves Zero-Shot Transfer from Synthetic Images.

Improving Knowledge Distillation Under Unknown Covariate Shift Through Confidence-Guided Data Augmentation Feature Distillation Improves Zero-Shot Transfer from Synthetic Images

Reference 32

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This paper cites Simple and Fast Group Robustness by Automatic Feature Reweighting.

Improving Knowledge Distillation Under Unknown Covariate Shift Through Confidence-Guided Data Augmentation Simple and Fast Group Robustness by Automatic Feature Reweighting

Reference 33

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Observation cf095a85-7725-4d0a-869c-057fc6566703 · outbound

This paper cites Learning Transferable Visual Models From Natural Language Supervision.

Improving Knowledge Distillation Under Unknown Covariate Shift Through Confidence-Guided Data Augmentation Learning Transferable Visual Models From Natural Language Supervision

Reference 34

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Observation 554dd6fd-fb30-41fb-82fb-f0fe1b0d04ca · outbound

This paper cites High-Resolution Image Synthesis with Latent Diffusion Models.

Improving Knowledge Distillation Under Unknown Covariate Shift Through Confidence-Guided Data Augmentation High-Resolution Image Synthesis with Latent Diffusion Models

Reference 35

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Observation b9ed77e4-9e9b-4936-98c4-deec6dfce990 · outbound

This paper cites ImageNet Large Scale Visual Recognition Challenge.

Improving Knowledge Distillation Under Unknown Covariate Shift Through Confidence-Guided Data Augmentation ImageNet Large Scale Visual Recognition Challenge

Reference 36

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Observation dcebbdc5-92bb-49db-b959-767f93c648f1 · outbound

This paper cites Distributionally Robust Neural Networks.

Improving Knowledge Distillation Under Unknown Covariate Shift Through Confidence-Guided Data Augmentation Distributionally Robust Neural Networks

Reference 37

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This paper cites Does Knowledge Distillation Really Work?.

Improving Knowledge Distillation Under Unknown Covariate Shift Through Confidence-Guided Data Augmentation Does Knowledge Distillation Really Work?

Reference 38

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Observation df4d0279-0a78-48d7-a4d8-94619eb2c4a7 · outbound

This paper cites Effective Data Augmentation With Diffusion Models.

Improving Knowledge Distillation Under Unknown Covariate Shift Through Confidence-Guided Data Augmentation Effective Data Augmentation With Diffusion Models

Reference 39

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This paper cites Group Robust Classification Without Any Group Information.

Improving Knowledge Distillation Under Unknown Covariate Shift Through Confidence-Guided Data Augmentation Group Robust Classification Without Any Group Information

Reference 40

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Observation 0b955a47-a7e6-417b-b334-287e218ab0ae · outbound

This paper cites Efficient Knowledge Distillation from Model Checkpoints.

Improving Knowledge Distillation Under Unknown Covariate Shift Through Confidence-Guided Data Augmentation Efficient Knowledge Distillation from Model Checkpoints

Reference 41

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Observation 8df0a97b-86fb-4760-b09b-a883d55f9086 · outbound

This paper cites What Makes a.

Improving Knowledge Distillation Under Unknown Covariate Shift Through Confidence-Guided Data Augmentation What Makes a

Reference 42

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Observation ebb613d9-e39d-482f-89a6-cbc20ba2319e · outbound

This paper cites Label-Free Neural Semantic Image Synthesis.

Improving Knowledge Distillation Under Unknown Covariate Shift Through Confidence-Guided Data Augmentation Label-Free Neural Semantic Image Synthesis

Reference 43

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Observation cf0fc3f2-e24c-48f4-a24f-7d984b1ace0e · outbound

This paper cites https://github.com/rwightman/pytorch- image-models.

Improving Knowledge Distillation Under Unknown Covariate Shift Through Confidence-Guided Data Augmentation https://github.com/rwightman/pytorch- image-models

Reference 44

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Observation 7faa4d48-be7e-4250-9974-ac011f23e133 · outbound

This paper cites ResNet strikes back: An improved training procedure in timm.

Improving Knowledge Distillation Under Unknown Covariate Shift Through Confidence-Guided Data Augmentation ResNet strikes back: An improved training procedure in timm

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:35:22.865046Z

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Observation 3d6038b3-e02e-4295-bf87-e49d9f932ea1 · outbound

This paper cites FreeMask: Synthetic Images with Dense Annotations Make Stronger Segmentation Models.

Improving Knowledge Distillation Under Unknown Covariate Shift Through Confidence-Guided Data Augmentation FreeMask: Synthetic Images with Dense Annotations Make Stronger Segmentation Models

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:35:22.670645Z

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Observation 44937388-c3b3-4be7-835c-0bb329f22720 · outbound

This paper cites CutMix: Regularization Strategy to Train Strong Classifiers With Localizable Features.

Improving Knowledge Distillation Under Unknown Covariate Shift Through Confidence-Guided Data Augmentation CutMix: Regularization Strategy to Train Strong Classifiers With Localizable Features

Reference 47

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Observation 7082d4eb-0e54-49d2-a539-faad7abc189e · outbound

This paper cites Efficient Bias Mitigation Without Privileged Information.

Improving Knowledge Distillation Under Unknown Covariate Shift Through Confidence-Guided Data Augmentation Efficient Bias Mitigation Without Privileged Information

Reference 48

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Observation cc7353c4-6eae-4dd4-865f-1bfd2de94924 · outbound

This paper cites Mixup: Beyond Empirical Risk Minimization.

Improving Knowledge Distillation Under Unknown Covariate Shift Through Confidence-Guided Data Augmentation Mixup: Beyond Empirical Risk Minimization

Reference 49

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Observation e3bf8dff-41e2-4008-bfcb-e924c8b90628 · outbound

This paper cites Expanding Small-Scale Datasets with Guided Imagination.

Improving Knowledge Distillation Under Unknown Covariate Shift Through Confidence-Guided Data Augmentation Expanding Small-Scale Datasets with Guided Imagination

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:35:21.935940Z

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Observation cdb125d7-a2d0-4025-aa6c-fd7403252865 · outbound

This paper cites DatasetGAN: Efficient Labeled Data Factory With Minimal Human Effort.

Improving Knowledge Distillation Under Unknown Covariate Shift Through Confidence-Guided Data Augmentation DatasetGAN: Efficient Labeled Data Factory With Minimal Human Effort

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:35:21.698393Z

Source-reported events for the cited work

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Observation b41995d1-6304-486d-910d-e383d7cff55e · outbound

This paper cites Distribution-Aware Data Expansion with Diffusion Models.

Improving Knowledge Distillation Under Unknown Covariate Shift Through Confidence-Guided Data Augmentation Distribution-Aware Data Expansion with Diffusion Models

Reference 52

Resolution: malformed identifier; raw_fallback, observed 2026-08-07T11:35:21.537889Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 7df42da3-6816-467b-8974-d24bf9d392bf · outbound

This paper cites a realistic photo of a{classname}.

Improving Knowledge Distillation Under Unknown Covariate Shift Through Confidence-Guided Data Augmentation a realistic photo of a{classname}

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:35:21.371594Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Coverage vector

Reference resolution

Outbound references

Pith citing papers