Secure Transfer Learning: Training Clean Models Against Backdoor in (Both) Pre-trained Encoders and Downstream Datasets | Paper Citation Record

Observation 68635449-04ab-4e17-96cf-81db51fd8dde · outbound

This paper cites Badnets: Evaluating backdooring attacks on deep neural networks,.

Secure Transfer Learning: Training Clean Models Against Backdoor in (Both) Pre-trained Encoders and Downstream Datasets Badnets: Evaluating backdooring attacks on deep neural networks,

Reference 1

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Observation 70989984-4f38-45e0-a58a-999c337fc2cc · outbound

This paper cites Targeted Backdoor Attacks on Deep Learning Systems Using Data Poisoning.

Secure Transfer Learning: Training Clean Models Against Backdoor in (Both) Pre-trained Encoders and Downstream Datasets Targeted Backdoor Attacks on Deep Learning Systems Using Data Poisoning

Reference 2

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Observation aceb65e3-039b-4363-806e-a4757b93649e · outbound

This paper cites Badclip: Dual-embedding guided backdoor attack on multimodal contrastive learning,.

Secure Transfer Learning: Training Clean Models Against Backdoor in (Both) Pre-trained Encoders and Downstream Datasets Badclip: Dual-embedding guided backdoor attack on multimodal contrastive learning,

Reference 3

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Observation e78cf9a1-97b7-4256-803a-26ea23f154cb · outbound

This paper cites BadEncoder: Backdoor Attacks to Pre-trained Encoders in Self-Supervised Learning,.

Secure Transfer Learning: Training Clean Models Against Backdoor in (Both) Pre-trained Encoders and Downstream Datasets BadEncoder: Backdoor Attacks to Pre-trained Encoders in Self-Supervised Learning,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:40:54.269527Z

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Observation 91eb603a-74bf-4e18-9703-d76d4204ad0b · outbound

This paper cites Backdoor Attacks Against Transfer Learning With Pre-Trained Deep Learning Models,.

Secure Transfer Learning: Training Clean Models Against Backdoor in (Both) Pre-trained Encoders and Downstream Datasets Backdoor Attacks Against Transfer Learning With Pre-Trained Deep Learning Models,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:40:54.258404Z

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Observation 0b27a2ad-c8d1-44f4-a375-798332751a84 · outbound

This paper cites An em- barrassingly simple backdoor attack on self-supervised learning,.

Secure Transfer Learning: Training Clean Models Against Backdoor in (Both) Pre-trained Encoders and Downstream Datasets An em- barrassingly simple backdoor attack on self-supervised learning,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:40:54.248096Z

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Observation 76cc3693-40a2-447e-ad93-6edd5186904f · outbound

This paper cites Dis- tribution Preserving Backdoor Attack in Self-supervised Learning,.

Secure Transfer Learning: Training Clean Models Against Backdoor in (Both) Pre-trained Encoders and Downstream Datasets Dis- tribution Preserving Backdoor Attack in Self-supervised Learning,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:40:54.237642Z

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Observation c9061f37-3833-4b77-ae39-5bc50b00cb04 · outbound

This paper cites Back- door attacks on self-supervised learning,.

Secure Transfer Learning: Training Clean Models Against Backdoor in (Both) Pre-trained Encoders and Downstream Datasets Back- door attacks on self-supervised learning,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:40:54.227321Z

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Observation 33fe8cc6-e2dd-45fd-a61e-86166ae33e12 · outbound

This paper cites CorruptEncoder: Data poi- soning based backdoor attacks to contrastive learning,.

Secure Transfer Learning: Training Clean Models Against Backdoor in (Both) Pre-trained Encoders and Downstream Datasets CorruptEncoder: Data poi- soning based backdoor attacks to contrastive learning,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:40:54.217288Z

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Observation d1ddf10a-7321-42f6-8e4a-d081a1080edc · outbound

This paper cites A new backdoor attack in cnns by training set corruption without label poisoning,.

Secure Transfer Learning: Training Clean Models Against Backdoor in (Both) Pre-trained Encoders and Downstream Datasets A new backdoor attack in cnns by training set corruption without label poisoning,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:40:54.206406Z

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Observation 9e89d05e-be81-48af-a29a-3ebf656b09c0 · outbound

This paper cites Demon in the variant: Statistical analysis of DNNs for robust backdoor contamination de- tection,.

Secure Transfer Learning: Training Clean Models Against Backdoor in (Both) Pre-trained Encoders and Downstream Datasets Demon in the variant: Statistical analysis of DNNs for robust backdoor contamination de- tection,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:40:54.196382Z

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Observation d49f2884-af98-44bb-b071-fb95b7345876 · outbound

This paper cites Revisiting the assumption of latent separability for backdoor defenses,.

Secure Transfer Learning: Training Clean Models Against Backdoor in (Both) Pre-trained Encoders and Downstream Datasets Revisiting the assumption of latent separability for backdoor defenses,

Reference 12

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Observation 6122eaec-126d-40ca-9a3a-807e8afa59f3 · outbound

This paper cites WaNet - imperceptible warping- based backdoor attack,.

Secure Transfer Learning: Training Clean Models Against Backdoor in (Both) Pre-trained Encoders and Downstream Datasets WaNet - imperceptible warping- based backdoor attack,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:40:54.173973Z

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Observation 8fef750f-88b5-4393-96c5-4c9b0a661564 · outbound

This paper cites Backdoor defense via deconfounded representation learning,.

Secure Transfer Learning: Training Clean Models Against Backdoor in (Both) Pre-trained Encoders and Downstream Datasets Backdoor defense via deconfounded representation learning,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:40:54.162641Z

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Observation 51c42ee2-e429-41d9-a461-fd4ac9a1106a · outbound

This paper cites Anti-Backdoor Learning: Training Clean Models on Poisoned Data,.

Secure Transfer Learning: Training Clean Models Against Backdoor in (Both) Pre-trained Encoders and Downstream Datasets Anti-Backdoor Learning: Training Clean Models on Poisoned Data,

Reference 15

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Observation d28c41d8-e9be-47d3-aa87-fe0d7026a62d · outbound

This paper cites SPECTRE: defending against backdoor attacks using robust statistics,.

Secure Transfer Learning: Training Clean Models Against Backdoor in (Both) Pre-trained Encoders and Downstream Datasets SPECTRE: defending against backdoor attacks using robust statistics,

Reference 16

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Observation 568a766d-9cfb-4561-832a-9e819ae9ec42 · outbound

This paper cites Data-free backdoor re- moval based on channel lipschitzness,.

Secure Transfer Learning: Training Clean Models Against Backdoor in (Both) Pre-trained Encoders and Downstream Datasets Data-free backdoor re- moval based on channel lipschitzness,

Reference 17

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Observation fcac6cfb-d47d-49ae-93aa-92aff80a3e4f · outbound

This paper cites Detecting Backdoor Attacks on Deep Neural Networks by Activation Clustering.

Secure Transfer Learning: Training Clean Models Against Backdoor in (Both) Pre-trained Encoders and Downstream Datasets Detecting Backdoor Attacks on Deep Neural Networks by Activation Clustering

Reference 18

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Observation 6f9fe05a-f0bd-4931-a0b9-c5d3987b58ac · outbound

This paper cites Spectral signatures in backdoor attacks,.

Secure Transfer Learning: Training Clean Models Against Backdoor in (Both) Pre-trained Encoders and Downstream Datasets Spectral signatures in backdoor attacks,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:40:54.122175Z

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Observation 26daba79-3c4d-4953-9d20-0884b2cae8b0 · outbound

This paper cites ASSET: Robust back- door data detection across a multiplicity of deep learning paradigms,.

Secure Transfer Learning: Training Clean Models Against Backdoor in (Both) Pre-trained Encoders and Downstream Datasets ASSET: Robust back- door data detection across a multiplicity of deep learning paradigms,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:40:54.112779Z

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Observation faf7ce1a-8464-4c77-8af7-4066097ace43 · outbound

This paper cites Towards a proactive ML approach for detecting backdoor poison samples,.

Secure Transfer Learning: Training Clean Models Against Backdoor in (Both) Pre-trained Encoders and Downstream Datasets Towards a proactive ML approach for detecting backdoor poison samples,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:40:54.102456Z

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Observation c3b0a8ad-3b2a-462e-b0b1-f02b5365a524 · outbound

This paper cites STRIP: A defence against trojan attacks on deep neural networks,.

Secure Transfer Learning: Training Clean Models Against Backdoor in (Both) Pre-trained Encoders and Downstream Datasets STRIP: A defence against trojan attacks on deep neural networks,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:40:54.091421Z

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Observation b5d9ee6e-661b-438a-add7-f999d30d7f62 · outbound

This paper cites IBD-PSC: Input-level backdoor detection via parameter-oriented scaling consis- tency,.

Secure Transfer Learning: Training Clean Models Against Backdoor in (Both) Pre-trained Encoders and Downstream Datasets IBD-PSC: Input-level backdoor detection via parameter-oriented scaling consis- tency,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:40:54.080781Z

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Observation 292f84cf-01bc-44f0-b05c-0895773e5488 · outbound

This paper cites SCALE- UP: An efficient black-box input-level backdoor detection via ana- lyzing scaled prediction consistency,.

Secure Transfer Learning: Training Clean Models Against Backdoor in (Both) Pre-trained Encoders and Downstream Datasets SCALE- UP: An efficient black-box input-level backdoor detection via ana- lyzing scaled prediction consistency,

Reference 24

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Observation 005f85b3-926b-4e42-b22f-e5882aeb6d03 · outbound

This paper cites Adversarial unlearning of backdoors via implicit hypergradient,.

Secure Transfer Learning: Training Clean Models Against Backdoor in (Both) Pre-trained Encoders and Downstream Datasets Adversarial unlearning of backdoors via implicit hypergradient,

Reference 25

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Observation f1d0884e-1e10-474a-9ca2-3d59867578a3 · outbound

This paper cites Enhancing fine-tuning based backdoor defense with sharpness-aware minimization,.

Secure Transfer Learning: Training Clean Models Against Backdoor in (Both) Pre-trained Encoders and Downstream Datasets Enhancing fine-tuning based backdoor defense with sharpness-aware minimization,

Reference 26

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Observation b60baa9f-7421-4e73-9019-3db945aca759 · outbound

This paper cites On the effectiveness of distil- lation in mitigating backdoors in pre-trained encoder,.

Secure Transfer Learning: Training Clean Models Against Backdoor in (Both) Pre-trained Encoders and Downstream Datasets On the effectiveness of distil- lation in mitigating backdoors in pre-trained encoder,

Reference 27

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Observation 8585adcf-07ba-48ce-b09b-8caa0c84295b · outbound

This paper cites Februus: Input purification defense against trojan attacks on deep neural network systems,.

Secure Transfer Learning: Training Clean Models Against Backdoor in (Both) Pre-trained Encoders and Downstream Datasets Februus: Input purification defense against trojan attacks on deep neural network systems,

Reference 28

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Observation b77f6b12-9f8a-4f82-8ce2-93988134e579 · outbound

This paper cites Backdoor Attack in the Physical World.

Secure Transfer Learning: Training Clean Models Against Backdoor in (Both) Pre-trained Encoders and Downstream Datasets Backdoor Attack in the Physical World

Reference 29

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This paper cites Deepsweep: An evaluation framework for mitigating dnn back- door attacks using data augmentation,.

Secure Transfer Learning: Training Clean Models Against Backdoor in (Both) Pre-trained Encoders and Downstream Datasets Deepsweep: An evaluation framework for mitigating dnn back- door attacks using data augmentation,

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:40:54.029703Z

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Observation 63f4fb9b-22d8-49aa-90a4-37edfd055b88 · outbound

This paper cites Detecting backdoors during the inference stage based on corruption robustness consistency,.

Secure Transfer Learning: Training Clean Models Against Backdoor in (Both) Pre-trained Encoders and Downstream Datasets Detecting backdoors during the inference stage based on corruption robustness consistency,

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:40:54.020496Z

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Observation 1bd531b7-290c-4c4b-8030-8ff2b103d694 · outbound

This paper cites Robust backdoor detection for deep learning via topo- logical evolution dynamics,.

Secure Transfer Learning: Training Clean Models Against Backdoor in (Both) Pre-trained Encoders and Downstream Datasets Robust backdoor detection for deep learning via topo- logical evolution dynamics,

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:40:54.010765Z

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Observation 1ed9887e-4ce5-4dd0-b0f2-cb4d3301dfb3 · outbound

This paper cites The ”Beat- rix.

Secure Transfer Learning: Training Clean Models Against Backdoor in (Both) Pre-trained Encoders and Downstream Datasets The ”Beat- rix

Reference 33

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Observation 5d648af8-3a7b-4299-b710-85e409cbe695 · outbound

This paper cites Backdoor defense via decoupling the training process,.

Secure Transfer Learning: Training Clean Models Against Backdoor in (Both) Pre-trained Encoders and Downstream Datasets Backdoor defense via decoupling the training process,

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:40:53.990992Z

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Observation 6cc559e9-ef90-4098-a3d6-662b34ce38db · outbound

This paper cites Training with more confi- dence: Mitigating injected and natural backdoors during training,.

Secure Transfer Learning: Training Clean Models Against Backdoor in (Both) Pre-trained Encoders and Downstream Datasets Training with more confi- dence: Mitigating injected and natural backdoors during training,

Reference 35

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Observation c06eaada-78e5-4dda-854e-168f18c535b1 · outbound

This paper cites Progressive poisoned data isolation for training-time backdoor defense,.

Secure Transfer Learning: Training Clean Models Against Backdoor in (Both) Pre-trained Encoders and Downstream Datasets Progressive poisoned data isolation for training-time backdoor defense,

Reference 36

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Observation fb6c4152-c906-4acc-9223-873fe7b52277 · outbound

This paper cites Fine-Pruning: Defending against backdooring attacks on deep neural networks,.

Secure Transfer Learning: Training Clean Models Against Backdoor in (Both) Pre-trained Encoders and Downstream Datasets Fine-Pruning: Defending against backdooring attacks on deep neural networks,

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:40:53.958543Z

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Observation e6aa3bc1-5e25-4517-9137-6b8a5050c78d · outbound

This paper cites Towards inspecting and eliminating trojan backdoors in deep neural networks,.

Secure Transfer Learning: Training Clean Models Against Backdoor in (Both) Pre-trained Encoders and Downstream Datasets Towards inspecting and eliminating trojan backdoors in deep neural networks,

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:40:53.947983Z

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Observation 8fdd1634-f0d8-422d-bb91-10c7f9bc5190 · outbound

This paper cites Backdoor scanning for deep neural networks through k- arm optimization,.

Secure Transfer Learning: Training Clean Models Against Backdoor in (Both) Pre-trained Encoders and Downstream Datasets Backdoor scanning for deep neural networks through k- arm optimization,

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:40:53.936765Z

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Observation 20b47d64-1d63-47a0-bcee-8981dc82553a · outbound

This paper cites Neural Cleanse: Identifying and mitigating backdoor attacks in neural networks,.

Secure Transfer Learning: Training Clean Models Against Backdoor in (Both) Pre-trained Encoders and Downstream Datasets Neural Cleanse: Identifying and mitigating backdoor attacks in neural networks,

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:40:53.924019Z

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Observation 1bcf2d21-5625-4786-8a87-4e7d6ff41d13 · outbound

This paper cites Detecting backdoors in pre-trained encoders,.

Secure Transfer Learning: Training Clean Models Against Backdoor in (Both) Pre-trained Encoders and Downstream Datasets Detecting backdoors in pre-trained encoders,

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:40:53.913473Z

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Observation d4ae4116-cb1d-4f4f-ae25-986a972e3e44 · outbound

This paper cites Backdoor defense via adaptively splitting poisoned dataset,.

Secure Transfer Learning: Training Clean Models Against Backdoor in (Both) Pre-trained Encoders and Downstream Datasets Backdoor defense via adaptively splitting poisoned dataset,

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:40:53.902938Z

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Observation e8df6a45-b4bf-4af2-94b8-e2a757191951 · outbound

This paper cites Model-agnostic meta-learning for fast adaptation of deep networks,.

Secure Transfer Learning: Training Clean Models Against Backdoor in (Both) Pre-trained Encoders and Downstream Datasets Model-agnostic meta-learning for fast adaptation of deep networks,

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:40:53.892024Z

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Observation cdb4d572-2682-4240-9a20-78c0145dbf02 · outbound

This paper cites Learning multiple layers of features from tiny im- ages,.

Secure Transfer Learning: Training Clean Models Against Backdoor in (Both) Pre-trained Encoders and Downstream Datasets Learning multiple layers of features from tiny im- ages,

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:40:53.881650Z

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Observation 922a3452-01d9-4d82-b984-64f6dc0158ee · outbound

This paper cites Man vs. computer: Benchmarking machine learning algorithms for traffic sign recognition,.

Secure Transfer Learning: Training Clean Models Against Backdoor in (Both) Pre-trained Encoders and Downstream Datasets Man vs. computer: Benchmarking machine learning algorithms for traffic sign recognition,

Reference 45

Resolution: unresolved; no resolver link, observed 2026-08-16T12:40:53.401040Z

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Observation 91341fa6-9000-4d59-9f1c-f0d81907ab5c · outbound

This paper cites Reading digits in natural images with unsupervised feature learning,.

Secure Transfer Learning: Training Clean Models Against Backdoor in (Both) Pre-trained Encoders and Downstream Datasets Reading digits in natural images with unsupervised feature learning,

Reference 46

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Observation 5cb907d6-bca8-4d0c-81e7-637be07e8f91 · outbound

This paper cites An analysis of single-layer networks in unsupervised feature learning,.

Secure Transfer Learning: Training Clean Models Against Backdoor in (Both) Pre-trained Encoders and Downstream Datasets An analysis of single-layer networks in unsupervised feature learning,

Reference 47

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Observation 7a62952f-d321-468f-b1e4-249f7c9373ad · outbound

This paper cites ImageNet: A large-scale hierarchical image database,.

Secure Transfer Learning: Training Clean Models Against Backdoor in (Both) Pre-trained Encoders and Downstream Datasets ImageNet: A large-scale hierarchical image database,

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:40:53.852621Z

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No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation c7f94922-d6d6-4b43-a01b-ea0d58cdc926 · outbound

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Secure Transfer Learning: Training Clean Models Against Backdoor in (Both) Pre-trained Encoders and Downstream Datasets META- SIFT : How to sift out a clean subset in the presence of data poi- soning?,

Reference 49

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This paper cites Mutual information guided backdoor mitigation for pre- trained encoders,.

Secure Transfer Learning: Training Clean Models Against Backdoor in (Both) Pre-trained Encoders and Downstream Datasets Mutual information guided backdoor mitigation for pre- trained encoders,

Reference 50

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This paper cites Mitigat- ing Backdoor Attacks in Pre-Trained Encoders via Self-Supervised Knowledge Distillation ,.

Secure Transfer Learning: Training Clean Models Against Backdoor in (Both) Pre-trained Encoders and Downstream Datasets Mitigat- ing Backdoor Attacks in Pre-Trained Encoders via Self-Supervised Knowledge Distillation ,

Reference 51

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This paper cites A density-based algorithm for discovering clusters in large spatial databases with noise,.

Secure Transfer Learning: Training Clean Models Against Backdoor in (Both) Pre-trained Encoders and Downstream Datasets A density-based algorithm for discovering clusters in large spatial databases with noise,

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:40:53.822024Z

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Secure Transfer Learning: Training Clean Models Against Backdoor in (Both) Pre-trained Encoders and Downstream Datasets Unresolved cited work

Reference 53

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Secure Transfer Learning: Training Clean Models Against Backdoor in (Both) Pre-trained Encoders and Downstream Datasets Unresolved cited work

Reference 54

Resolution: unresolved; raw_fallback, observed 2026-08-16T12:40:53.800650Z

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Secure Transfer Learning: Training Clean Models Against Backdoor in (Both) Pre-trained Encoders and Downstream Datasets Unresolved cited work

Reference 55

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Secure Transfer Learning: Training Clean Models Against Backdoor in (Both) Pre-trained Encoders and Downstream Datasets Unresolved cited work

Reference 56

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Secure Transfer Learning: Training Clean Models Against Backdoor in (Both) Pre-trained Encoders and Downstream Datasets Unresolved cited work

Reference 57

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This paper cites Car” for STL-10, “Bird.

Secure Transfer Learning: Training Clean Models Against Backdoor in (Both) Pre-trained Encoders and Downstream Datasets Car” for STL-10, “Bird

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:40:53.759892Z

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Secure Transfer Learning: Training Clean Models Against Backdoor in (Both) Pre-trained Encoders and Downstream Datasets Unresolved cited work

Reference 59

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Observation 6cc3a99c-304b-4111-87bf-e80ec6c83441 · outbound

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Secure Transfer Learning: Training Clean Models Against Backdoor in (Both) Pre-trained Encoders and Downstream Datasets Unresolved cited work

Reference 60

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Secure Transfer Learning: Training Clean Models Against Backdoor in (Both) Pre-trained Encoders and Downstream Datasets Unresolved cited work

Reference 61

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Secure Transfer Learning: Training Clean Models Against Backdoor in (Both) Pre-trained Encoders and Downstream Datasets Unresolved cited work

Reference 62

Resolution: unresolved; raw_fallback, observed 2026-08-16T12:40:53.715750Z

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Secure Transfer Learning: Training Clean Models Against Backdoor in (Both) Pre-trained Encoders and Downstream Datasets Unresolved cited work

Reference 63

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Secure Transfer Learning: Training Clean Models Against Backdoor in (Both) Pre-trained Encoders and Downstream Datasets Unresolved cited work

Reference 64

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Observation a220722e-a162-4efa-8632-baaf5d1b3f50 · outbound

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Secure Transfer Learning: Training Clean Models Against Backdoor in (Both) Pre-trained Encoders and Downstream Datasets Unresolved cited work

Reference 65

Resolution: unresolved; raw_fallback, observed 2026-08-16T12:40:53.682029Z

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Observation 4fd3c065-ff6f-4d79-aa34-d2f5ced5807d · outbound

This paper cites an unresolved cited work.

Secure Transfer Learning: Training Clean Models Against Backdoor in (Both) Pre-trained Encoders and Downstream Datasets Unresolved cited work

Reference 66

Resolution: unresolved; raw_fallback, observed 2026-08-16T12:40:53.671236Z

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This paper cites an unresolved cited work.

Secure Transfer Learning: Training Clean Models Against Backdoor in (Both) Pre-trained Encoders and Downstream Datasets Unresolved cited work

Reference 67

Resolution: unresolved; raw_fallback, observed 2026-08-16T12:40:53.659408Z

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Observation bc1bbd1a-1a02-4bbf-acec-a7d56b2ec861 · outbound

This paper cites an unresolved cited work.

Secure Transfer Learning: Training Clean Models Against Backdoor in (Both) Pre-trained Encoders and Downstream Datasets Unresolved cited work

Reference 68

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Coverage vector

Reference resolution

Outbound references

Pith citing papers