Targeting Negative Flips in Active Learning using Validation Sets | Paper Citation Record

Observation 402c5d2e-b4dc-4e83-9a00-10961646de47 · outbound

This paper cites Positive-Congruent Training: Towards Regression-Free Model Updates.

Targeting Negative Flips in Active Learning using Validation Sets Positive-Congruent Training: Towards Regression-Free Model Updates

Reference 1

Resolution: verified exact; local_arxiv, observed 2026-08-12T19:14:55.971205Z

Source-reported events for the cited work

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

Observation d867cdd4-4f1b-40b3-a905-7d9a74d1cbb4 · outbound

This paper cites CURE-TSR: Challenging unreal and real environments for traffic sign recognition,.

Targeting Negative Flips in Active Learning using Validation Sets CURE-TSR: Challenging unreal and real environments for traffic sign recognition,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:14:56.444569Z

Source-reported events for the cited work

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

Observation 2d02ad2d-1ee0-4b89-a7a3-081351822fa3 · outbound

This paper cites Active learning with statistical models,.

Targeting Negative Flips in Active Learning using Validation Sets Active learning with statistical models,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:14:56.431173Z

Source-reported events for the cited work

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

Observation f8a4ebd1-9aa4-4add-8a9f-2ffde75bab63 · outbound

This paper cites Tong, Active learning: theory and applications.

Targeting Negative Flips in Active Learning using Validation Sets Tong, Active learning: theory and applications

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:14:56.418733Z

Source-reported events for the cited work

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

Observation 8e060ae1-89ff-4276-8295-e1b9fb6492ea · outbound

This paper cites On learning, representing, and generalizing a task in a humanoid robot,.

Targeting Negative Flips in Active Learning using Validation Sets On learning, representing, and generalizing a task in a humanoid robot,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:14:56.406658Z

Source-reported events for the cited work

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

Observation 8facb76a-47de-4e84-9d94-5569b7ea7bae · outbound

This paper cites Scalable active learning for object detection,.

Targeting Negative Flips in Active Learning using Validation Sets Scalable active learning for object detection,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:14:56.393433Z

Source-reported events for the cited work

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

Observation 5a807312-c567-4e78-a73c-940f58454c93 · outbound

This paper cites Focal: A cost- aware video dataset for active learning,.

Targeting Negative Flips in Active Learning using Validation Sets Focal: A cost- aware video dataset for active learning,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:14:56.379454Z

Source-reported events for the cited work

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

Observation 4638b795-b1b2-450e-b01c-78e9b7abc2b7 · outbound

This paper cites Batch mode active learning and its application to medical image classification,.

Targeting Negative Flips in Active Learning using Validation Sets Batch mode active learning and its application to medical image classification,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:14:56.364686Z

Source-reported events for the cited work

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

Observation b8eec6fa-c43a-4f60-bbfc-ba0b16c2bb50 · outbound

This paper cites Patient Aware Active Learning for Fine-Grained OCT Classification.

Targeting Negative Flips in Active Learning using Validation Sets Patient Aware Active Learning for Fine-Grained OCT Classification

Reference 9

Resolution: verified exact; local_arxiv, observed 2026-08-12T19:14:55.953720Z

Source-reported events for the cited work

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

Observation 9ac98bec-92a9-47a5-9663-4d5d761f9bf9 · outbound

This paper cites Effective data selection for seismic interpretation through disagreement,.

Targeting Negative Flips in Active Learning using Validation Sets Effective data selection for seismic interpretation through disagreement,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:14:56.351134Z

Source-reported events for the cited work

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

Observation db43067b-4196-484d-986b-f3eb0aa3cd72 · outbound

This paper cites Clinical trial active learning,.

Targeting Negative Flips in Active Learning using Validation Sets Clinical trial active learning,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:14:56.336761Z

Source-reported events for the cited work

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

Observation 3a0413f6-69b2-41f0-b3e9-86dfdb2f38e1 · outbound

This paper cites DECAL: DEployable Clinical Active Learning.

Targeting Negative Flips in Active Learning using Validation Sets DECAL: DEployable Clinical Active Learning

Reference 12

Resolution: verified exact; local_arxiv, observed 2026-08-12T19:14:55.936221Z

Source-reported events for the cited work

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

Observation dc5547d9-f7af-461e-a976-f32b909a270e · outbound

This paper cites Generalization and parameter estimation in feedforward nets: Some experiments,.

Targeting Negative Flips in Active Learning using Validation Sets Generalization and parameter estimation in feedforward nets: Some experiments,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:14:56.323497Z

Source-reported events for the cited work

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

Observation 78760098-bf26-46f1-ab45-eaa5a3885c62 · outbound

This paper cites SIMILAR: Submodular Information Measures Based Active Learning In Realistic Scenarios.

Targeting Negative Flips in Active Learning using Validation Sets SIMILAR: Submodular Information Measures Based Active Learning In Realistic Scenarios

Reference 14

Resolution: verified exact; local_arxiv, observed 2026-08-12T19:14:55.917778Z

Source-reported events for the cited work

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

Observation f0a63720-e5fe-4a60-9eb4-e3b098d4eb92 · outbound

This paper cites Two faces of active learning,.

Targeting Negative Flips in Active Learning using Validation Sets Two faces of active learning,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:14:56.309791Z

Source-reported events for the cited work

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

Observation b3faade9-2343-4515-a248-cf0eaab956f1 · outbound

This paper cites Active learning literature survey,.

Targeting Negative Flips in Active Learning using Validation Sets Active learning literature survey,

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-12T19:14:55.496404Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5ba1fab4-0f5d-4d73-9b39-ea18fe80dac0 · outbound

This paper cites Theory of disagreement-based active learning,.

Targeting Negative Flips in Active Learning using Validation Sets Theory of disagreement-based active learning,

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-12T19:14:55.500702Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c7e29522-9a51-44da-af9f-fe72a1cf60b3 · outbound

This paper cites A new active labeling method for deep learning,.

Targeting Negative Flips in Active Learning using Validation Sets A new active labeling method for deep learning,

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-12T19:14:55.505137Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4dd1a36e-9e2a-46e2-adab-9e5275dc0cff · outbound

This paper cites Forgetful active learning with switch events: Efficient sampling for out-of-distribution data,.

Targeting Negative Flips in Active Learning using Validation Sets Forgetful active learning with switch events: Efficient sampling for out-of-distribution data,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:14:56.270651Z

Source-reported events for the cited work

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

Observation 86405ce9-193c-4dbf-a2f3-72e3e351f788 · outbound

This paper cites Margin-based active learning for structured out- put spaces,.

Targeting Negative Flips in Active Learning using Validation Sets Margin-based active learning for structured out- put spaces,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:14:56.257421Z

Source-reported events for the cited work

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

Observation afd74d1e-4e6b-469c-829d-4d1600d03c85 · outbound

This paper cites Less is more: Active learning with support vector machines,.

Targeting Negative Flips in Active Learning using Validation Sets Less is more: Active learning with support vector machines,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:14:56.244191Z

Source-reported events for the cited work

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

Observation 4ccef5e1-1e9c-4dec-907b-47f22a55010e · outbound

This paper cites Transitional Uncertainty with Layered Intermediate Predictions.

Targeting Negative Flips in Active Learning using Validation Sets Transitional Uncertainty with Layered Intermediate Predictions

Reference 22

Resolution: verified exact; local_arxiv, observed 2026-08-12T19:14:55.897706Z

Source-reported events for the cited work

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

Observation 30fe22c0-8203-41c8-85c0-eb2632bdcace · outbound

This paper cites Support vector machine active learning with applications to text classification,.

Targeting Negative Flips in Active Learning using Validation Sets Support vector machine active learning with applications to text classification,

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-12T19:14:55.525290Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 24c10a0e-0de0-41a7-9751-3c6aebd0b453 · outbound

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

Targeting Negative Flips in Active Learning using Validation Sets The power of ensembles for active learning in image classification,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:14:56.221399Z

Source-reported events for the cited work

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

Observation 8ee0fbdb-7e9a-4b0c-a18e-2d643287958b · outbound

This paper cites Bayesian Active Learning for Classification and Preference Learning.

Targeting Negative Flips in Active Learning using Validation Sets Bayesian Active Learning for Classification and Preference Learning

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-12T19:14:55.532318Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 95a3a228-b65a-4f41-94a3-c74eb5c567ad · outbound

This paper cites Active Learning for Convolutional Neural Networks: A Core-Set Approach.

Targeting Negative Flips in Active Learning using Validation Sets Active Learning for Convolutional Neural Networks: A Core-Set Approach

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-12T19:14:55.536039Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e8d5120f-8a00-4285-a512-4392718dae6e · outbound

This paper cites Deep Active Learning over the Long Tail.

Targeting Negative Flips in Active Learning using Validation Sets Deep Active Learning over the Long Tail

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-12T19:14:55.540232Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8dc12405-b1ff-4082-beff-c7582e0093c4 · outbound

This paper cites Discriminative Active Learning.

Targeting Negative Flips in Active Learning using Validation Sets Discriminative Active Learning

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-12T19:14:55.544422Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0c4bd5c0-f7d4-4ff4-b6dc-41124bb5da60 · outbound

This paper cites Deep Batch Active Learning by Diverse, Uncertain Gradient Lower Bounds.

Targeting Negative Flips in Active Learning using Validation Sets Deep Batch Active Learning by Diverse, Uncertain Gradient Lower Bounds

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-12T19:14:55.548737Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5a6fa88b-b77c-4c94-aae4-34c2bd8b8a65 · outbound

This paper cites Gaussian switch sampling: A second order approach to active learning,.

Targeting Negative Flips in Active Learning using Validation Sets Gaussian switch sampling: A second order approach to active learning,

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:14:56.207903Z

Source-reported events for the cited work

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

Observation 9355a16a-6c3d-4099-823f-1e71b4bed641 · outbound

This paper cites Active Learning in Bayesian Neural Networks with Balanced Entropy Learning Principle.

Targeting Negative Flips in Active Learning using Validation Sets Active Learning in Bayesian Neural Networks with Balanced Entropy Learning Principle

Reference 31

Resolution: verified exact; local_arxiv, observed 2026-08-12T19:14:55.807770Z

Source-reported events for the cited work

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

Observation f6e84ed3-6124-4566-a82e-2c26275404a6 · outbound

This paper cites BatchBALD: Efficient and Diverse Batch Acquisition for Deep Bayesian Active Learning.

Targeting Negative Flips in Active Learning using Validation Sets BatchBALD: Efficient and Diverse Batch Acquisition for Deep Bayesian Active Learning

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-12T19:14:55.561571Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 75aceb67-8637-43de-84c0-cb16063704c4 · outbound

This paper cites Stochastic Batch Acquisition: A Simple Baseline for Deep Active Learning.

Targeting Negative Flips in Active Learning using Validation Sets Stochastic Batch Acquisition: A Simple Baseline for Deep Active Learning

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-12T19:14:55.566238Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9edc9232-675e-4821-a3a0-193baeacb431 · outbound

This paper cites Lifelong machine learning,.

Targeting Negative Flips in Active Learning using Validation Sets Lifelong machine learning,

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:14:56.194669Z

Source-reported events for the cited work

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

Observation f731c1f0-3e02-497d-93fd-0aec6a31a594 · outbound

This paper cites Online structured laplace approxi- mations for overcoming catastrophic forgetting,.

Targeting Negative Flips in Active Learning using Validation Sets Online structured laplace approxi- mations for overcoming catastrophic forgetting,

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:14:56.181710Z

Source-reported events for the cited work

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

Observation 69ca5438-1f1b-4b9d-80f1-d6e2c638fadb · outbound

This paper cites An Empirical Study of Example Forgetting during Deep Neural Network Learning.

Targeting Negative Flips in Active Learning using Validation Sets An Empirical Study of Example Forgetting during Deep Neural Network Learning

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-12T19:14:55.587308Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 200b36bb-1a85-4009-bf82-d713c4e09b25 · outbound

This paper cites Gdumb: A simple approach that questions our progress in continual learning,.

Targeting Negative Flips in Active Learning using Validation Sets Gdumb: A simple approach that questions our progress in continual learning,

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:14:56.169676Z

Source-reported events for the cited work

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

Observation 1d67d465-94ce-4422-9138-8e6d0a4d41fc · outbound

This paper cites Learning without forgetting,.

Targeting Negative Flips in Active Learning using Validation Sets Learning without forgetting,

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-12T19:14:55.596606Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3788b660-c96e-462e-99fd-3434711b15c8 · outbound

This paper cites Towards open set deep networks,.

Targeting Negative Flips in Active Learning using Validation Sets Towards open set deep networks,

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-12T19:14:55.600578Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b2af73cc-9f03-4814-94e8-bd25f1f1135b · outbound

This paper cites Toward open set recognition,.

Targeting Negative Flips in Active Learning using Validation Sets Toward open set recognition,

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:14:56.140333Z

Source-reported events for the cited work

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

Observation 1c0d5e41-0f20-4a60-a31b-a8a60a956f55 · outbound

This paper cites Open-set recognition with gradient-based representations,.

Targeting Negative Flips in Active Learning using Validation Sets Open-set recognition with gradient-based representations,

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:14:56.126514Z

Source-reported events for the cited work

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

Observation 8cdadbcc-179c-4eb0-8533-f7a9793a5778 · outbound

This paper cites Backprop- agated gradient representations for anomaly detection,.

Targeting Negative Flips in Active Learning using Validation Sets Backprop- agated gradient representations for anomaly detection,

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:14:56.113009Z

Source-reported events for the cited work

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

Observation 933c4be0-2eb0-4169-834c-0c90f20599e7 · outbound

This paper cites Memory aware synapses: Learning what (not) to forget,.

Targeting Negative Flips in Active Learning using Validation Sets Memory aware synapses: Learning what (not) to forget,

Reference 44

Resolution: unresolved; no resolver link, observed 2026-08-12T19:14:55.616679Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bb2322e5-2baa-4d0e-8049-28fea031b293 · outbound

This paper cites Overcoming catastrophic forgetting in incremental few-shot learning by finding flat minima,.

Targeting Negative Flips in Active Learning using Validation Sets Overcoming catastrophic forgetting in incremental few-shot learning by finding flat minima,

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:14:56.090905Z

Source-reported events for the cited work

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

Observation d14a8bd6-fb11-49be-aa44-d6a1d8169c01 · outbound

This paper cites Explainable seismic neural networks using learning statistics,.

Targeting Negative Flips in Active Learning using Validation Sets Explainable seismic neural networks using learning statistics,

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:14:56.077590Z

Source-reported events for the cited work

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

Observation bbe27397-058b-4bde-b412-0cf66ffdd37a · outbound

This paper cites Explaining deep models through forgettable learning dynamics,.

Targeting Negative Flips in Active Learning using Validation Sets Explaining deep models through forgettable learning dynamics,

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:14:56.064066Z

Source-reported events for the cited work

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

Observation 73b77d25-1cde-4f2b-ae66-7445e5a9b99a · outbound

This paper cites Example forgetting: A novel approach to explain and interpret deep neural networks in seismic interpretation,.

Targeting Negative Flips in Active Learning using Validation Sets Example forgetting: A novel approach to explain and interpret deep neural networks in seismic interpretation,

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:14:56.050310Z

Source-reported events for the cited work

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

Observation 0ee997fa-50ec-4528-bd52-a34477f16f2f · outbound

This paper cites Distilling the Knowledge in a Neural Network.

Targeting Negative Flips in Active Learning using Validation Sets Distilling the Knowledge in a Neural Network

Reference 49

Resolution: unresolved; no resolver link, observed 2026-08-12T19:14:55.635528Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7e848a21-3220-441d-8ef3-6ccc3164d366 · outbound

This paper cites Dropout as a bayesian approximation: Representing model uncertainty in deep learning,.

Targeting Negative Flips in Active Learning using Validation Sets Dropout as a bayesian approximation: Representing model uncertainty in deep learning,

Reference 50

Resolution: unresolved; no resolver link, observed 2026-08-12T19:14:55.638915Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e4eea344-cdd2-48dc-8b86-77ff04edc726 · outbound

This paper cites Simple and scalable predictive uncertainty estimation using deep ensembles,.

Targeting Negative Flips in Active Learning using Validation Sets Simple and scalable predictive uncertainty estimation using deep ensembles,

Reference 51

Resolution: unresolved; no resolver link, observed 2026-08-12T19:14:55.642266Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 04ddc48e-e584-4d56-823e-cdf3cb272558 · outbound

This paper cites Energy-based out-of- distribution detection,.

Targeting Negative Flips in Active Learning using Validation Sets Energy-based out-of- distribution detection,

Reference 52

Resolution: unresolved; no resolver link, observed 2026-08-12T19:14:55.645784Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 65c26e4c-9282-4d5f-a3ae-f6b841b1cc5d · outbound

This paper cites Deep bayesian active learning with image data,.

Targeting Negative Flips in Active Learning using Validation Sets Deep bayesian active learning with image data,

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:14:56.010981Z

Source-reported events for the cited work

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

Observation 38089998-3e18-4bae-a1cf-44cdc3cd0b5b · outbound

This paper cites Learning multiple layers of features from tiny images,.

Targeting Negative Flips in Active Learning using Validation Sets Learning multiple layers of features from tiny images,

Reference 54

Resolution: unresolved; no resolver link, observed 2026-08-12T19:14:55.652802Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 03a7619f-1720-411b-8bfb-9416c9ebcd2b · outbound

This paper cites Tiny imagenet visual recognition challenge,.

Targeting Negative Flips in Active Learning using Validation Sets Tiny imagenet visual recognition challenge,

Reference 56

Resolution: unresolved; no resolver link, observed 2026-08-12T19:14:55.664313Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a5ec02e8-9d74-4394-96e8-589d7c091333 · outbound

This paper cites Deep residual learning for image recognition,.

Targeting Negative Flips in Active Learning using Validation Sets Deep residual learning for image recognition,

Reference 57

Resolution: unresolved; no resolver link, observed 2026-08-12T19:14:55.668305Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 47080050-c399-40f6-94da-f62a0ec90bd0 · outbound

This paper cites Patches Are All You Need?.

Targeting Negative Flips in Active Learning using Validation Sets Patches Are All You Need?

Reference 58

Resolution: unresolved; no resolver link, observed 2026-08-12T19:14:55.672250Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cbe2e56b-40d1-4eab-9fa7-a93f5b8d5967 · outbound

This paper cites Overcoming catastrophic forgetting in neural networks.

Targeting Negative Flips in Active Learning using Validation Sets Overcoming catastrophic forgetting in neural networks

Reference 2016

Resolution: unresolved; no resolver link, observed 2026-08-12T19:14:55.579091Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 542369a1-7c0c-4471-8197-fdb0df338225 · outbound

This paper cites CINIC-10 is not ImageNet or CIFAR-10.

Targeting Negative Flips in Active Learning using Validation Sets CINIC-10 is not ImageNet or CIFAR-10

Reference 2018

Resolution: unresolved; no resolver link, observed 2026-08-12T19:14:55.660385Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Coverage vector

Reference resolution

Outbound references

Pith citing papers