Uncertainty-Driven Hierarchical Sampling for Unbalanced Continual Malware Detection with Time-Series Update-Based Retrieval | Paper Citation Record

Observation 65485d3e-1d1f-4fc0-9f41-d28aba9b7feb · outbound

This paper cites Continuous learning for Android malware detection.

Uncertainty-Driven Hierarchical Sampling for Unbalanced Continual Malware Detection with Time-Series Update-Based Retrieval Continuous learning for Android malware detection

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T22:06:39.950731Z

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Observation 48d36bd3-5368-45bb-94de-abc02152fa8a · outbound

This paper cites Automated, reliable zero- day malware detection based on autoencoding architecture.

Uncertainty-Driven Hierarchical Sampling for Unbalanced Continual Malware Detection with Time-Series Update-Based Retrieval Automated, reliable zero- day malware detection based on autoencoding architecture

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T22:06:39.942993Z

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Observation 85dd0669-cf12-4f40-bdc3-ce774f8d44ef · outbound

This paper cites ArchSentry: Enhanced Android Malware Detection via Hierarchical Semantic Ex- traction.

Uncertainty-Driven Hierarchical Sampling for Unbalanced Continual Malware Detection with Time-Series Update-Based Retrieval ArchSentry: Enhanced Android Malware Detection via Hierarchical Semantic Ex- traction

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T22:06:39.934574Z

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Observation 204dad11-23dc-4375-8c9c-c1b0cb331373 · outbound

This paper cites Entropy-based sample selection for online contin- ual learning.

Uncertainty-Driven Hierarchical Sampling for Unbalanced Continual Malware Detection with Time-Series Update-Based Retrieval Entropy-based sample selection for online contin- ual learning

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T22:06:39.926741Z

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Observation cb2b77c7-a66e-4b5b-8306-cde4abb9abfe · outbound

This paper cites Active learning literature survey.

Uncertainty-Driven Hierarchical Sampling for Unbalanced Continual Malware Detection with Time-Series Update-Based Retrieval Active learning literature survey

Reference 5

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Observation 2d7c42df-4ede-4f99-ba69-8c51acaa1554 · outbound

This paper cites Uncertainty in deep learning.

Uncertainty-Driven Hierarchical Sampling for Unbalanced Continual Malware Detection with Time-Series Update-Based Retrieval Uncertainty in deep learning

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T22:06:39.914480Z

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Observation c900b9d8-8d4d-4e1b-9699-a77478db2006 · outbound

This paper cites The power of ensembles for active learning in image classification.

Uncertainty-Driven Hierarchical Sampling for Unbalanced Continual Malware Detection with Time-Series Update-Based Retrieval The power of ensembles for active learning in image classification

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T22:06:39.906683Z

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Observation ffc0dbfe-9847-4430-b893-11a570b6e709 · outbound

This paper cites Discriminative Active Learning.

Uncertainty-Driven Hierarchical Sampling for Unbalanced Continual Malware Detection with Time-Series Update-Based Retrieval Discriminative Active Learning

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-04T22:06:38.570181Z

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Observation eb590e13-5845-4a73-94d7-fd51be0490a4 · outbound

This paper cites Semi-supervised learning with variational Bayesian inference and maximum uncertainty regularization.

Uncertainty-Driven Hierarchical Sampling for Unbalanced Continual Malware Detection with Time-Series Update-Based Retrieval Semi-supervised learning with variational Bayesian inference and maximum uncertainty regularization

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T22:06:39.899357Z

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Observation 742eca19-b87c-413b-a77b-ad2a6ece49e7 · outbound

This paper cites Uncertainty-based continual learning with adaptive regularization.Advances in Neural Information Processing Systems, 2019, 32.

Uncertainty-Driven Hierarchical Sampling for Unbalanced Continual Malware Detection with Time-Series Update-Based Retrieval Uncertainty-based continual learning with adaptive regularization.Advances in Neural Information Processing Systems, 2019, 32

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T22:06:39.892238Z

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Observation e0877796-7ae7-4c5d-8a94-9b8273b92e21 · outbound

This paper cites Transcending TRANSCEND: Revisiting malware classification in the presence of concept drift.2022 IEEE Symposium on Security and Privacy (SP), 2022: 805-823.

Uncertainty-Driven Hierarchical Sampling for Unbalanced Continual Malware Detection with Time-Series Update-Based Retrieval Transcending TRANSCEND: Revisiting malware classification in the presence of concept drift.2022 IEEE Symposium on Security and Privacy (SP), 2022: 805-823

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T22:06:39.884237Z

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Observation 413d4d20-930e-46fb-ad2d-e90a79ba0a15 · outbound

This paper cites Overcoming catastrophic forgetting in neural networks.Proceedings of the National Academy of Sciences, 2017, 114(13): 3521-3526.

Uncertainty-Driven Hierarchical Sampling for Unbalanced Continual Malware Detection with Time-Series Update-Based Retrieval Overcoming catastrophic forgetting in neural networks.Proceedings of the National Academy of Sciences, 2017, 114(13): 3521-3526

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T22:06:39.876440Z

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Observation f5e0c58c-fb4b-4303-a2a0-248ad3c2bea2 · outbound

This paper cites Progressive Neural Networks.

Uncertainty-Driven Hierarchical Sampling for Unbalanced Continual Malware Detection with Time-Series Update-Based Retrieval Progressive Neural Networks

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-04T22:06:38.903708Z

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Observation ccdcd802-84af-4513-9773-98161d7a5064 · outbound

This paper cites iCaRL: Incremental classifier and representation learning.

Uncertainty-Driven Hierarchical Sampling for Unbalanced Continual Malware Detection with Time-Series Update-Based Retrieval iCaRL: Incremental classifier and representation learning

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T22:06:39.868337Z

Source-reported events for the cited work

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Observation 32835fa0-177e-435a-95eb-05bb513983c2 · outbound

This paper cites DER: Dynamically expandable representation for class incremental learning.

Uncertainty-Driven Hierarchical Sampling for Unbalanced Continual Malware Detection with Time-Series Update-Based Retrieval DER: Dynamically expandable representation for class incremental learning

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T22:06:39.861136Z

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Observation 60e8605c-32aa-4a8d-93fe-3d07a5dc09fe · outbound

This paper cites PODNet: Pooled outputs distil- lation for small-tasks incremental learning.

Uncertainty-Driven Hierarchical Sampling for Unbalanced Continual Malware Detection with Time-Series Update-Based Retrieval PODNet: Pooled outputs distil- lation for small-tasks incremental learning

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T22:06:39.853248Z

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Observation 06f0204c-29af-4f33-8e51-d66a01807648 · outbound

This paper cites Toward deep super- vised anomaly detection: Reinforcement learning from partially labeled anomaly data.

Uncertainty-Driven Hierarchical Sampling for Unbalanced Continual Malware Detection with Time-Series Update-Based Retrieval Toward deep super- vised anomaly detection: Reinforcement learning from partially labeled anomaly data

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T22:06:39.845118Z

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Observation 21daebbd-7f8c-40a9-9ba9-038967cdbfd8 · outbound

This paper cites Towards Building Generalizable Models for Malware Detection.

Uncertainty-Driven Hierarchical Sampling for Unbalanced Continual Malware Detection with Time-Series Update-Based Retrieval Towards Building Generalizable Models for Malware Detection

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T22:06:39.837870Z

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Observation 1d527f45-13a0-4ede-a457-e558c31a630b · outbound

This paper cites Improving adversarial robustness using knowledge distillation guided by attention information bottleneck.

Uncertainty-Driven Hierarchical Sampling for Unbalanced Continual Malware Detection with Time-Series Update-Based Retrieval Improving adversarial robustness using knowledge distillation guided by attention information bottleneck

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T22:06:39.830144Z

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Observation affea943-b7cc-4dd0-831f-b10e4c2e4bd1 · outbound

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

Uncertainty-Driven Hierarchical Sampling for Unbalanced Continual Malware Detection with Time-Series Update-Based Retrieval Model-agnostic meta-learning for fast adaptation of deep networks

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T22:06:39.822571Z

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Observation cf1a4f74-63e0-4b19-8b5f-fdd01547d1fd · outbound

This paper cites Prototypical networks for few-shot learning.Advances in Neural Information Processing Systems, 2017, 30.

Uncertainty-Driven Hierarchical Sampling for Unbalanced Continual Malware Detection with Time-Series Update-Based Retrieval Prototypical networks for few-shot learning.Advances in Neural Information Processing Systems, 2017, 30

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T22:06:39.814410Z

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Observation e5c96f80-80b8-4534-af59-89712712f88e · outbound

This paper cites Learning to compare: Relation network for few-shot learning.

Uncertainty-Driven Hierarchical Sampling for Unbalanced Continual Malware Detection with Time-Series Update-Based Retrieval Learning to compare: Relation network for few-shot learning

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T22:06:39.806466Z

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Observation 56f9aab7-8ee6-4451-8e7f-2dfb12cb267d · outbound

This paper cites Meta-baseline: Exploring simple meta- learning for few-shot learning.

Uncertainty-Driven Hierarchical Sampling for Unbalanced Continual Malware Detection with Time-Series Update-Based Retrieval Meta-baseline: Exploring simple meta- learning for few-shot learning

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T22:06:39.799176Z

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Observation 79a75e0c-03e6-4621-84e7-6af0b050ad8f · outbound

This paper cites A Baseline for Few-Shot Image Classification.

Uncertainty-Driven Hierarchical Sampling for Unbalanced Continual Malware Detection with Time-Series Update-Based Retrieval A Baseline for Few-Shot Image Classification

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-04T22:06:39.476046Z

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Observation 288fc271-0d42-4656-ba26-84b9f9f8f7d0 · outbound

This paper cites Meta-learning for multi-family android malware classification.ACM Transactions on Software Engineering and Methodology, 2024, 33(7): 1-27.

Uncertainty-Driven Hierarchical Sampling for Unbalanced Continual Malware Detection with Time-Series Update-Based Retrieval Meta-learning for multi-family android malware classification.ACM Transactions on Software Engineering and Methodology, 2024, 33(7): 1-27

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T22:06:39.791742Z

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Observation 49d1d912-c833-4e88-af10-8c1b3f450e64 · outbound

This paper cites NF-GNN: Network flow graph neural networks for malware detection and classification.

Uncertainty-Driven Hierarchical Sampling for Unbalanced Continual Malware Detection with Time-Series Update-Based Retrieval NF-GNN: Network flow graph neural networks for malware detection and classification

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T22:06:39.784160Z

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Observation a6db91a7-f3c5-43b0-89a7-64f85ca1f4e3 · outbound

This paper cites FewM-HGCL: Few-shot malware variants de- tection via heterogeneous graph contrastive learning.IEEE Transactions on Dependable and Secure Computing, 2022.

Uncertainty-Driven Hierarchical Sampling for Unbalanced Continual Malware Detection with Time-Series Update-Based Retrieval FewM-HGCL: Few-shot malware variants de- tection via heterogeneous graph contrastive learning.IEEE Transactions on Dependable and Secure Computing, 2022

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T22:06:39.776575Z

Source-reported events for the cited work

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Observation 45c5ce1e-de92-403a-a0ff-d5ec1c10a814 · outbound

This paper cites Few-shot class-incremental learning.

Uncertainty-Driven Hierarchical Sampling for Unbalanced Continual Malware Detection with Time-Series Update-Based Retrieval Few-shot class-incremental learning

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T22:06:39.768825Z

Source-reported events for the cited work

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Observation 3930ed5b-27a9-4c75-833a-19a55995c576 · outbound

This paper cites Incremental few-shot learning with attention attractor networks.Adv.

Uncertainty-Driven Hierarchical Sampling for Unbalanced Continual Malware Detection with Time-Series Update-Based Retrieval Incremental few-shot learning with attention attractor networks.Adv

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T22:06:39.761963Z

Source-reported events for the cited work

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Observation 994aa342-35d5-4c94-bdef-7aafbb3ba249 · outbound

This paper cites Few-shot lifelong learning.Proc.

Uncertainty-Driven Hierarchical Sampling for Unbalanced Continual Malware Detection with Time-Series Update-Based Retrieval Few-shot lifelong learning.Proc

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T22:06:39.754894Z

Source-reported events for the cited work

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Observation 9db8edd3-1e37-4880-8b6a-cb6a8340803b · outbound

This paper cites Self-promoted prototype refinement for few-shot class-incremental learning.

Uncertainty-Driven Hierarchical Sampling for Unbalanced Continual Malware Detection with Time-Series Update-Based Retrieval Self-promoted prototype refinement for few-shot class-incremental learning

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T22:06:39.747966Z

Source-reported events for the cited work

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Observation 850e4499-125a-43d9-a2d8-3bf949872873 · outbound

This paper cites Semantic-aware knowledge distillation for few-shot class incremental learning.

Uncertainty-Driven Hierarchical Sampling for Unbalanced Continual Malware Detection with Time-Series Update-Based Retrieval Semantic-aware knowledge distillation for few-shot class incremental learning

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T22:06:39.739887Z

Source-reported events for the cited work

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Observation 305b35a8-daae-4894-9080-d0cadd3592ee · outbound

This paper cites An incremental malware classification approach based on few-shot learning.

Uncertainty-Driven Hierarchical Sampling for Unbalanced Continual Malware Detection with Time-Series Update-Based Retrieval An incremental malware classification approach based on few-shot learning

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T22:06:39.732624Z

Source-reported events for the cited work

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Observation ce25736c-4a64-4522-b79b-0f2fe241b173 · outbound

This paper cites Forward compatible few-shot class- incremental learning.

Uncertainty-Driven Hierarchical Sampling for Unbalanced Continual Malware Detection with Time-Series Update-Based Retrieval Forward compatible few-shot class- incremental learning

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T22:06:39.725271Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation ad804256-8f13-4310-929e-f4be42e06a7d · outbound

This paper cites Few-shot class-incremental learning via relation knowledge distillation.

Uncertainty-Driven Hierarchical Sampling for Unbalanced Continual Malware Detection with Time-Series Update-Based Retrieval Few-shot class-incremental learning via relation knowledge distillation

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T22:06:39.718074Z

Source-reported events for the cited work

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Observation 41def54b-fac8-412d-9685-7ad790cca3ab · outbound

This paper cites GPTree: A Gaussian process classifier for few-shot incremental learning.

Uncertainty-Driven Hierarchical Sampling for Unbalanced Continual Malware Detection with Time-Series Update-Based Retrieval GPTree: A Gaussian process classifier for few-shot incremental learning

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T22:06:39.710761Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation c022fb4d-12f0-4c5a-80af-87843615a87c · outbound

This paper cites Few-shot class-incremental learning via compact and separable features for fine-grained vehicle recognition.IEEE Trans.

Uncertainty-Driven Hierarchical Sampling for Unbalanced Continual Malware Detection with Time-Series Update-Based Retrieval Few-shot class-incremental learning via compact and separable features for fine-grained vehicle recognition.IEEE Trans

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T22:06:39.703253Z

Source-reported events for the cited work

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Observation dc2498ec-6c90-425a-9927-68f05bd79408 · outbound

This paper cites Evidential deep learning to quantify classification uncertainty.Advances in Neural Information Processing Systems, 2018, 31.

Uncertainty-Driven Hierarchical Sampling for Unbalanced Continual Malware Detection with Time-Series Update-Based Retrieval Evidential deep learning to quantify classification uncertainty.Advances in Neural Information Processing Systems, 2018, 31

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T22:06:39.695019Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation a5b3922f-753b-4316-8eb9-97eb227f8cb2 · outbound

This paper cites In:Computers in Biology and Medicine.

Uncertainty-Driven Hierarchical Sampling for Unbalanced Continual Malware Detection with Time-Series Update-Based Retrieval In:Computers in Biology and Medicine

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T22:06:39.687110Z

Source-reported events for the cited work

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Observation a2c0a772-8656-4d11-b60e-72ab52e0b16b · outbound

This paper cites EVIL: Evidential inference learning for trustworthy semi-supervised medical image seg- mentation.

Uncertainty-Driven Hierarchical Sampling for Unbalanced Continual Malware Detection with Time-Series Update-Based Retrieval EVIL: Evidential inference learning for trustworthy semi-supervised medical image seg- mentation

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T22:06:39.679352Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 704e235d-f402-4b40-8098-c491f0938b38 · outbound

This paper cites Patient-level anatomy meets scanning-level physics: Personalized federated low-dose ct denoising empowered by large language model.

Uncertainty-Driven Hierarchical Sampling for Unbalanced Continual Malware Detection with Time-Series Update-Based Retrieval Patient-level anatomy meets scanning-level physics: Personalized federated low-dose ct denoising empowered by large language model

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T22:06:39.671622Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 0f0ce0e3-2740-4848-97b6-e8f67856f3d7 · outbound

This paper cites Enhancing state-of-the-art classifiers with API semantics to detect evolved Android malware.

Uncertainty-Driven Hierarchical Sampling for Unbalanced Continual Malware Detection with Time-Series Update-Based Retrieval Enhancing state-of-the-art classifiers with API semantics to detect evolved Android malware

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T22:06:39.663958Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 02b92ddf-d0c7-45cf-88ac-1b9135cc4be8 · outbound

This paper cites https://androzoo.uni.lu/.

Uncertainty-Driven Hierarchical Sampling for Unbalanced Continual Malware Detection with Time-Series Update-Based Retrieval https://androzoo.uni.lu/

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T22:06:39.655995Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation fcaa7663-173b-4e0e-b92c-75b3b124aca9 · outbound

This paper cites https://www.virustotal.com/.

Uncertainty-Driven Hierarchical Sampling for Unbalanced Continual Malware Detection with Time-Series Update-Based Retrieval https://www.virustotal.com/

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T22:06:39.648400Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation c723c9c8-5e65-46f2-910a-58c7ae8313f5 · outbound

This paper cites https://virusshare.com/.

Uncertainty-Driven Hierarchical Sampling for Unbalanced Continual Malware Detection with Time-Series Update-Based Retrieval https://virusshare.com/

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T22:06:39.640597Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 0598815e-104e-47bb-8007-f8cb4c3964ff · outbound

This paper cites Dos and don’ts of machine learning in computer security.

Uncertainty-Driven Hierarchical Sampling for Unbalanced Continual Malware Detection with Time-Series Update-Based Retrieval Dos and don’ts of machine learning in computer security

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T22:06:39.632144Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 311e4d75-2058-4fa2-8b43-5c3440f9cfa9 · outbound

This paper cites AndroZoo: Collecting millions of Android apps for the research community.

Uncertainty-Driven Hierarchical Sampling for Unbalanced Continual Malware Detection with Time-Series Update-Based Retrieval AndroZoo: Collecting millions of Android apps for the research community

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T22:06:39.617155Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 9f9bb037-dc0f-403b-89f9-5531c0bca6fd · outbound

This paper cites Deep ground truth analysis of current Android malware.

Uncertainty-Driven Hierarchical Sampling for Unbalanced Continual Malware Detection with Time-Series Update-Based Retrieval Deep ground truth analysis of current Android malware

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T22:06:39.604266Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 67a6abad-9e8f-493f-a61c-e49abe9f9511 · outbound

This paper cites BODMAS: An open dataset for learning based temporal analysis of PE malware.

Uncertainty-Driven Hierarchical Sampling for Unbalanced Continual Malware Detection with Time-Series Update-Based Retrieval BODMAS: An open dataset for learning based temporal analysis of PE malware

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T22:06:39.596333Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 36a323df-94a5-451f-81f6-037e58cad773 · outbound

This paper cites CADE: Detecting and explaining concept drift samples for security applications.

Uncertainty-Driven Hierarchical Sampling for Unbalanced Continual Malware Detection with Time-Series Update-Based Retrieval CADE: Detecting and explaining concept drift samples for security applications

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T22:06:39.586265Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Coverage vector

Reference resolution

Outbound references

Pith citing papers