Multi-Label Bayesian Active Learning with Inter-Label Relationships | Paper Citation Record

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This paper cites A review of uncertainty quantification in deep learning: Techniques, applications and challenges.

Multi-Label Bayesian Active Learning with Inter-Label Relationships A review of uncertainty quantification in deep learning: Techniques, applications and challenges

Reference 1

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This paper cites Rebalancing label distribution while eliminating inherent waiting time in multi label active learning applied to transformers.

Multi-Label Bayesian Active Learning with Inter-Label Relationships Rebalancing label distribution while eliminating inherent waiting time in multi label active learning applied to transformers

Reference 2

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This paper cites Toward label-efficient neural network training: Diversity-based sampling in semi-supervised active learning.

Multi-Label Bayesian Active Learning with Inter-Label Relationships Toward label-efficient neural network training: Diversity-based sampling in semi-supervised active learning

Reference 3

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This paper cites Loss functions for binary class probability estimation and classification: Structure and applications.

Multi-Label Bayesian Active Learning with Inter-Label Relationships Loss functions for binary class probability estimation and classification: Structure and applications

Reference 4

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This paper cites Improved multi-label classification under temporal concept drift: Rethinking group-robust algorithms in a label-wise setting.

Multi-Label Bayesian Active Learning with Inter-Label Relationships Improved multi-label classification under temporal concept drift: Rethinking group-robust algorithms in a label-wise setting

Reference 5

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This paper cites Multieurlex-a multi-lingual and multi-label legal document classification dataset for zero-shot cross-lingual transfer.

Multi-Label Bayesian Active Learning with Inter-Label Relationships Multieurlex-a multi-lingual and multi-label legal document classification dataset for zero-shot cross-lingual transfer

Reference 6

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This paper cites Active bias: Training more accurate neural networks by emphasizing high variance samples.

Multi-Label Bayesian Active Learning with Inter-Label Relationships Active bias: Training more accurate neural networks by emphasizing high variance samples

Reference 7

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This paper cites Addressing imbalance in multilabel classification: Measures and random resampling algorithms.

Multi-Label Bayesian Active Learning with Inter-Label Relationships Addressing imbalance in multilabel classification: Measures and random resampling algorithms

Reference 8

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This paper cites Stable matching-based two-way selection in multi-label active learning with imbalanced data.

Multi-Label Bayesian Active Learning with Inter-Label Relationships Stable matching-based two-way selection in multi-label active learning with imbalanced data

Reference 9

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This paper cites Active learning for bert: an empirical study.

Multi-Label Bayesian Active Learning with Inter-Label Relationships Active learning for bert: an empirical study

Reference 10

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This paper cites Gradient descent finds global minima of deep neural networks.

Multi-Label Bayesian Active Learning with Inter-Label Relationships Gradient descent finds global minima of deep neural networks

Reference 11

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This paper cites The lottery ticket hypothesis: Finding sparse, trainable neural networks.

Multi-Label Bayesian Active Learning with Inter-Label Relationships The lottery ticket hypothesis: Finding sparse, trainable neural networks

Reference 12

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This paper cites Strictly proper scoring rules, prediction, and estimation.

Multi-Label Bayesian Active Learning with Inter-Label Relationships Strictly proper scoring rules, prediction, and estimation

Reference 13

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This paper cites An online active multi-label classification algorithm based on a hybrid label query strategy.

Multi-Label Bayesian Active Learning with Inter-Label Relationships An online active multi-label classification algorithm based on a hybrid label query strategy

Reference 14

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This paper cites Plvi-ce: a multi-label active learning algorithm with simultaneously considering uncertainty and diversity.

Multi-Label Bayesian Active Learning with Inter-Label Relationships Plvi-ce: a multi-label active learning algorithm with simultaneously considering uncertainty and diversity

Reference 15

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This paper cites Feature mixing-based active learning for multi-label text classification.

Multi-Label Bayesian Active Learning with Inter-Label Relationships Feature mixing-based active learning for multi-label text classification

Reference 16

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This paper cites Deal: Deep evidential active learning for image classification.

Multi-Label Bayesian Active Learning with Inter-Label Relationships Deal: Deep evidential active learning for image classification

Reference 17

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This paper cites Uncertainty-based active learning by bayesian u-net for multi-label cone-beam ct segmentation.

Multi-Label Bayesian Active Learning with Inter-Label Relationships Uncertainty-based active learning by bayesian u-net for multi-label cone-beam ct segmentation

Reference 18

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This paper cites Multi-label classification by exploiting local positive and negative pairwise label correlation.

Multi-Label Bayesian Active Learning with Inter-Label Relationships Multi-label classification by exploiting local positive and negative pairwise label correlation

Reference 19

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This paper cites Local positive and negative label correlation analysis with label awareness for multi-label classification.

Multi-Label Bayesian Active Learning with Inter-Label Relationships Local positive and negative label correlation analysis with label awareness for multi-label classification

Reference 20

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This paper cites Active query driven by uncertainty and diversity for incremental multi-label learning.

Multi-Label Bayesian Active Learning with Inter-Label Relationships Active query driven by uncertainty and diversity for incremental multi-label learning

Reference 21

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This paper cites Mimic-iii, a freely accessible critical care database.

Multi-Label Bayesian Active Learning with Inter-Label Relationships Mimic-iii, a freely accessible critical care database

Reference 22

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This paper cites Active learning with complementary sampling for instructing class-biased multi-label text emotion classification.

Multi-Label Bayesian Active Learning with Inter-Label Relationships Active learning with complementary sampling for instructing class-biased multi-label text emotion classification

Reference 23

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This paper cites An exploration of encoder-decoder approaches to multi-label classification for legal and biomedical text.

Multi-Label Bayesian Active Learning with Inter-Label Relationships An exploration of encoder-decoder approaches to multi-label classification for legal and biomedical text

Reference 24

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This paper cites Re-thinking federated active learning based on inter-class diversity.

Multi-Label Bayesian Active Learning with Inter-Label Relationships Re-thinking federated active learning based on inter-class diversity

Reference 25

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This paper cites Rcv1: A new benchmark collection for text categorization research.

Multi-Label Bayesian Active Learning with Inter-Label Relationships Rcv1: A new benchmark collection for text categorization research

Reference 26

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This paper cites Active learning with multi-label svm classification.

Multi-Label Bayesian Active Learning with Inter-Label Relationships Active learning with multi-label svm classification

Reference 27

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This paper cites Neuralclassifier: an open-source neural hierarchical multi-label text classification toolkit.

Multi-Label Bayesian Active Learning with Inter-Label Relationships Neuralclassifier: an open-source neural hierarchical multi-label text classification toolkit

Reference 28

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This paper cites Recurrent neural network for text classification with multi-task learning.

Multi-Label Bayesian Active Learning with Inter-Label Relationships Recurrent neural network for text classification with multi-task learning

Reference 29

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This paper cites Influence selection for active learning.

Multi-Label Bayesian Active Learning with Inter-Label Relationships Influence selection for active learning

Reference 30

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This paper cites Decoupled weight decay regularization.

Multi-Label Bayesian Active Learning with Inter-Label Relationships Decoupled weight decay regularization

Reference 31

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This paper cites Multi-label few/zero-shot learning with knowledge aggregated from multiple label graphs.

Multi-Label Bayesian Active Learning with Inter-Label Relationships Multi-label few/zero-shot learning with knowledge aggregated from multiple label graphs

Reference 32

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This paper cites Combining graph transformers based multi-label active learning and informative data augmentation for chest xray classification.

Multi-Label Bayesian Active Learning with Inter-Label Relationships Combining graph transformers based multi-label active learning and informative data augmentation for chest xray classification

Reference 33

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This paper cites Multi-label active learning through serial--parallel neural networks.

Multi-Label Bayesian Active Learning with Inter-Label Relationships Multi-label active learning through serial--parallel neural networks

Reference 34

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Multi-Label Bayesian Active Learning with Inter-Label Relationships o llenbrok and Beg \

Reference 35

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This paper cites o llenbrok, Gencer Sumbul, and Beg \.

Multi-Label Bayesian Active Learning with Inter-Label Relationships o llenbrok, Gencer Sumbul, and Beg \

Reference 36

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This paper cites Active learning for hierarchical multi-label classification.

Multi-Label Bayesian Active Learning with Inter-Label Relationships Active learning for hierarchical multi-label classification

Reference 37

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This paper cites Pytorch: An imperative style, high-performance deep learning library.

Multi-Label Bayesian Active Learning with Inter-Label Relationships Pytorch: An imperative style, high-performance deep learning library

Reference 38

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Multi-Label Bayesian Active Learning with Inter-Label Relationships Negative correlation learning in the extreme learning machine framework

Reference 39

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This paper cites Sampling bias in deep active classification: An empirical study.

Multi-Label Bayesian Active Learning with Inter-Label Relationships Sampling bias in deep active classification: An empirical study

Reference 40

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This paper cites A survey of deep active learning.

Multi-Label Bayesian Active Learning with Inter-Label Relationships A survey of deep active learning

Reference 41

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This paper cites Toward optimal active learning through sampling estimation of error reduction.

Multi-Label Bayesian Active Learning with Inter-Label Relationships Toward optimal active learning through sampling estimation of error reduction

Reference 42

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This paper cites Distilbert, a distilled version of bert: smaller, faster, cheaper and lighter.

Multi-Label Bayesian Active Learning with Inter-Label Relationships Distilbert, a distilled version of bert: smaller, faster, cheaper and lighter

Reference 43

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This paper cites A gaussian process-bayesian bernoulli mixture model for multi-label active learning.

Multi-Label Bayesian Active Learning with Inter-Label Relationships A gaussian process-bayesian bernoulli mixture model for multi-label active learning

Reference 44

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This paper cites Study of uncertainty quantification using multi-label ecg in deep learning models.

Multi-Label Bayesian Active Learning with Inter-Label Relationships Study of uncertainty quantification using multi-label ecg in deep learning models

Reference 45

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This paper cites Rethinking deep active learning: Using unlabeled data at model training.

Multi-Label Bayesian Active Learning with Inter-Label Relationships Rethinking deep active learning: Using unlabeled data at model training

Reference 46

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This paper cites Cost-efficient multi-instance multi-label active learning via correlation of features.

Multi-Label Bayesian Active Learning with Inter-Label Relationships Cost-efficient multi-instance multi-label active learning via correlation of features

Reference 47

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This paper cites Harnessing the power of beta scoring in deep active learning for multi-label text classification.

Multi-Label Bayesian Active Learning with Inter-Label Relationships Harnessing the power of beta scoring in deep active learning for multi-label text classification

Reference 48

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This paper cites Vaswani, N.

Multi-Label Bayesian Active Learning with Inter-Label Relationships Vaswani, N

Reference 49

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This paper cites Attribute and label distribution driven multi-label active learning.

Multi-Label Bayesian Active Learning with Inter-Label Relationships Attribute and label distribution driven multi-label active learning

Reference 50

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This paper cites Towards fewer annotations: Active learning via region impurity and prediction uncertainty for domain adaptive semantic segmentation.

Multi-Label Bayesian Active Learning with Inter-Label Relationships Towards fewer annotations: Active learning via region impurity and prediction uncertainty for domain adaptive semantic segmentation

Reference 51

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This paper cites Effective multi-label active learning for text classification.

Multi-Label Bayesian Active Learning with Inter-Label Relationships Effective multi-label active learning for text classification

Reference 52

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Observation 8a41bc06-47af-4b74-8f19-7a37730ddedb · outbound

This paper cites Not all out-of-distribution data are harmful to open-set active learning.

Multi-Label Bayesian Active Learning with Inter-Label Relationships Not all out-of-distribution data are harmful to open-set active learning

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:45:05.873774Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 73771ce5-740a-45c9-8140-a361bd418026 · outbound

This paper cites Rethinking the value of labels for improving class-imbalanced learning.

Multi-Label Bayesian Active Learning with Inter-Label Relationships Rethinking the value of labels for improving class-imbalanced learning

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:45:05.862564Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 10ff4e15-5fb2-4a74-a2cf-58729eb75455 · outbound

This paper cites An overview of overfitting and its solutions.

Multi-Label Bayesian Active Learning with Inter-Label Relationships An overview of overfitting and its solutions

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:45:05.850064Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 135ed3aa-b3a5-4892-a79b-3461257d4bf6 · outbound

This paper cites Cmal: Cost-effective multi-label active learning by querying subexamples.

Multi-Label Bayesian Active Learning with Inter-Label Relationships Cmal: Cost-effective multi-label active learning by querying subexamples

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:45:05.836483Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 5105bac9-6e28-4581-86e3-975303c01201 · outbound

This paper cites A sensitivity analysis of (and practitioners’ guide to) convolutional neural networks for sentence classification.

Multi-Label Bayesian Active Learning with Inter-Label Relationships A sensitivity analysis of (and practitioners’ guide to) convolutional neural networks for sentence classification

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:45:05.824440Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 4a76e5af-ba28-4d37-8373-31ca0b2d6d5c · outbound

This paper cites Granular multilabel batch active learning with pairwise label correlation.

Multi-Label Bayesian Active Learning with Inter-Label Relationships Granular multilabel batch active learning with pairwise label correlation

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:45:05.812186Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation ec3c342d-b9a5-46ca-8ad6-034e7e2f6e21 · outbound

This paper cites Uncertainty in bayesian deep label distribution learning.

Multi-Label Bayesian Active Learning with Inter-Label Relationships Uncertainty in bayesian deep label distribution learning

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:45:05.801110Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 3ef4d017-1b2e-47f6-81dc-4ec00d394c22 · outbound

This paper cites Addressing the item cold-start problem by attribute-driven active learning.

Multi-Label Bayesian Active Learning with Inter-Label Relationships Addressing the item cold-start problem by attribute-driven active learning

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:45:05.788821Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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