Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-07T04:16:10.868554Z
Paper Citation Record · LEDGER
Sampling Imbalanced Data with Multi-objective Bilevel Optimization
As of 20 August 2026, this Paper Citation Record lists 49 of 49 outbound references and 0 inbound Pith citation observations for arXiv:2506.11315.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
Reference resolution
49 of 49 outbound references displayed
- verified exact5
- verified fuzzy36
- unresolved8
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation 263b5a2d-960e-4841-9e3c-f7bea58e5ed8 · outbound
This paper cites Enhancing and improving the performance of imbalanced class data using novel GBO and SSG: A comparative analysis.
Sampling Imbalanced Data with Multi-objective Bilevel Optimization Enhancing and improving the performance of imbalanced class data using novel GBO and SSG: A comparative analysis
Reference 1
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T04:16:11.489639Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation ca0b83ed-7822-44d5-8ecf-0479580d6c0d · outbound
This paper cites RN-SMOTE: Reduced Noise SMOTE based on DBSCAN for enhancing imbalanced data classification.
Sampling Imbalanced Data with Multi-objective Bilevel Optimization RN-SMOTE: Reduced Noise SMOTE based on DBSCAN for enhancing imbalanced data classification
Reference 2
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T04:16:11.480592Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation cd62fb51-2262-4640-9d6e-0652bbb6b4bd · outbound
This paper cites Effective data-balancing methods for class-imbalanced genotoxicity datasets using machine learning algorithms and molecular fingerprints.
Sampling Imbalanced Data with Multi-objective Bilevel Optimization Effective data-balancing methods for class-imbalanced genotoxicity datasets using machine learning algorithms and molecular fingerprints
Reference 3
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T04:16:11.471074Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation cc0aa3ad-3bae-4c89-9ef0-7b96cd454f3a · outbound
This paper cites an unresolved cited work.
Sampling Imbalanced Data with Multi-objective Bilevel Optimization Unresolved cited work
Reference 4
- Resolution
- unresolved
- raw_fallback, observed 2026-08-07T04:16:11.461573Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 391e9689-d577-4aba-ac48-8a497f599cf9 · outbound
This paper cites an unresolved cited work.
Sampling Imbalanced Data with Multi-objective Bilevel Optimization Unresolved cited work
Reference 5
- Resolution
- unresolved
- raw_fallback, observed 2026-08-07T04:16:11.452495Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation a422ae58-953d-4106-b445-8d6a6b6b4a92 · outbound
This paper cites Addressing class imbalance in deep learning for small lesion detection on medical images.
Sampling Imbalanced Data with Multi-objective Bilevel Optimization Addressing class imbalance in deep learning for small lesion detection on medical images
Reference 6
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T04:16:11.442598Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 805ae936-5501-4c15-9b2b-10de62676b66 · outbound
This paper cites Imbalanced multi-label data classification as a bi-level optimization problem: application to miRNA-related diseases diagnosis.
Sampling Imbalanced Data with Multi-objective Bilevel Optimization Imbalanced multi-label data classification as a bi-level optimization problem: application to miRNA-related diseases diagnosis
Reference 7
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T04:16:11.432040Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 5aae77f3-6a92-4de0-9adc-b9d28e52ae1d · outbound
This paper cites an unresolved cited work.
Sampling Imbalanced Data with Multi-objective Bilevel Optimization Unresolved cited work
Reference 8
- Resolution
- unresolved
- raw_fallback, observed 2026-08-07T04:16:11.414702Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 48e2aa32-4465-4780-98d0-48cf4acd57aa · outbound
This paper cites Enhancing Financial Fraud Detection through Addressing Class Imbalance Using Hybrid SMOTE-GAN Techniques.
Sampling Imbalanced Data with Multi-objective Bilevel Optimization Enhancing Financial Fraud Detection through Addressing Class Imbalance Using Hybrid SMOTE-GAN Techniques
Reference 9
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T04:16:11.397925Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 60fd2b07-575a-4a0c-a1b6-65d976d5db0e · outbound
This paper cites Inverse Weight-Balancing for Deep Long-Tailed Learning.
Sampling Imbalanced Data with Multi-objective Bilevel Optimization Inverse Weight-Balancing for Deep Long-Tailed Learning
Reference 10
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T04:16:11.382483Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 9dd14050-dbde-4f64-a1c9-0c30c0855c8a · outbound
This paper cites On Supervised Class-Imbalanced Learning: An Updated Perspective and Some Key Challenges.IEEE Transactions on Artificial Intelligence, 3(6):973–993, December 2022.
Sampling Imbalanced Data with Multi-objective Bilevel Optimization On Supervised Class-Imbalanced Learning: An Updated Perspective and Some Key Challenges.IEEE Transactions on Artificial Intelligence, 3(6):973–993, December 2022
Reference 11
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T04:16:11.372077Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation ad9288f2-f41c-4432-aab5-6ab99be71271 · outbound
This paper cites The mnist database of handwritten digit images for machine learning research [best of the web].
Sampling Imbalanced Data with Multi-objective Bilevel Optimization The mnist database of handwritten digit images for machine learning research [best of the web]
Reference 12
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T04:16:10.761935Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 2f12c7a7-6a23-4a7c-8f3e-03bafe9f92e4 · outbound
This paper cites Leveraging GANs data augmentation for imbalanced medical image classification.
Sampling Imbalanced Data with Multi-objective Bilevel Optimization Leveraging GANs data augmentation for imbalanced medical image classification
Reference 13
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T04:16:11.356070Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation b5e63c67-2659-4bfb-8ecc-5a4f2ebc453c · outbound
This paper cites Legan: Addressing intraclass imbalance in gan-based medical image augmentation for improved imbalanced data classification.
Sampling Imbalanced Data with Multi-objective Bilevel Optimization Legan: Addressing intraclass imbalance in gan-based medical image augmentation for improved imbalanced data classification
Reference 14
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T04:16:11.346269Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation be75a5fc-73c3-409e-ae9e-d829dc25c4c3 · outbound
This paper cites Class-imbalanced semi-supervised learning with adaptive thresholding.
Sampling Imbalanced Data with Multi-objective Bilevel Optimization Class-imbalanced semi-supervised learning with adaptive thresholding
Reference 15
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T04:16:11.336494Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 5c61f1ef-a3d8-448b-8436-e98d8ccb3b87 · outbound
This paper cites Learning from class-imbalanced data: Review of methods and applications.
Sampling Imbalanced Data with Multi-objective Bilevel Optimization Learning from class-imbalanced data: Review of methods and applications
Reference 16
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T04:16:11.327250Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation d63197e3-c6a1-4fa3-95f6-4df300ebbdc8 · outbound
This paper cites Feature construction as a bi-level optimization problem.
Sampling Imbalanced Data with Multi-objective Bilevel Optimization Feature construction as a bi-level optimization problem
Reference 17
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T04:16:11.317952Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation ff817976-4bdf-4239-b5e9-4dd633ce0668 · outbound
This paper cites Borderline-SMOTE: A New Over-Sampling Method in Imbalanced Data Sets Learning.
Sampling Imbalanced Data with Multi-objective Bilevel Optimization Borderline-SMOTE: A New Over-Sampling Method in Imbalanced Data Sets Learning
Reference 18
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T04:16:11.308723Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 80c457e9-8f80-47c2-8695-6e0797572356 · outbound
This paper cites Jeni, Jeffrey F.
Sampling Imbalanced Data with Multi-objective Bilevel Optimization Jeni, Jeffrey F
Reference 19
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T04:16:11.299576Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation f2f6ea61-22f8-4557-a450-09640af266bd · outbound
This paper cites Johnson and Taghi M.
Sampling Imbalanced Data with Multi-objective Bilevel Optimization Johnson and Taghi M
Reference 20
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T04:16:11.290236Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 0bf8c033-e193-41cb-95a3-dd9b69bfb526 · outbound
This paper cites A Survey of Deep Learning based Online Transactions Fraud Detection Systems.
Sampling Imbalanced Data with Multi-objective Bilevel Optimization A Survey of Deep Learning based Online Transactions Fraud Detection Systems
Reference 21
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T04:16:11.280754Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 23aa7c4f-c576-4d89-9649-6361fe68c98e · outbound
This paper cites The uci machine learning repository.
Sampling Imbalanced Data with Multi-objective Bilevel Optimization The uci machine learning repository
Reference 22
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T04:16:11.271558Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 81b786c5-fc23-416c-a9ff-6e9bdb13de7c · outbound
This paper cites Khan, Munawar Hayat, Mohammed Bennamoun, Ferdous A.
Sampling Imbalanced Data with Multi-objective Bilevel Optimization Khan, Munawar Hayat, Mohammed Bennamoun, Ferdous A
Reference 23
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T04:16:11.262895Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation bfd1eeda-88ae-4636-8b2d-95c6c162f401 · outbound
This paper cites Adam: A Method for Stochastic Optimization.
Sampling Imbalanced Data with Multi-objective Bilevel Optimization Adam: A Method for Stochastic Optimization
Reference 24
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T04:16:10.798181Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 4f9c4ea7-2597-4201-9a50-83bfdf35e21d · outbound
This paper cites Deep learning-based imbalanced data classification for drug discovery.
Sampling Imbalanced Data with Multi-objective Bilevel Optimization Deep learning-based imbalanced data classification for drug discovery
Reference 25
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T04:16:11.253946Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation a09d227f-7638-4c01-aaa9-6ae17dd3c870 · outbound
This paper cites An empirical comparison and evaluation of minority oversampling techniques on a large number of imbalanced datasets.
Sampling Imbalanced Data with Multi-objective Bilevel Optimization An empirical comparison and evaluation of minority oversampling techniques on a large number of imbalanced datasets
Reference 26
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T04:16:11.244859Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 6b577413-d35e-4970-b034-953300fa1671 · outbound
This paper cites Classification of Imbalanced Data:Review of Methods and Applications.
Sampling Imbalanced Data with Multi-objective Bilevel Optimization Classification of Imbalanced Data:Review of Methods and Applications
Reference 27
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T04:16:11.235782Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 028b4f0a-664c-4e45-a4e5-f13c0cf6e441 · outbound
This paper cites AutoBalance: Optimized Loss Functions for Imbalanced Data.
Sampling Imbalanced Data with Multi-objective Bilevel Optimization AutoBalance: Optimized Loss Functions for Imbalanced Data
Reference 28
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T04:16:10.810396Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 6e555fd2-3086-4027-b892-4fc177863b29 · outbound
This paper cites DARTS: Differentiable Architecture Search, April.
Sampling Imbalanced Data with Multi-objective Bilevel Optimization DARTS: Differentiable Architecture Search, April
Reference 29
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T04:16:11.226839Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 4cefbd19-15a5-4b99-971e-56072ef1492c · outbound
This paper cites A hybrid sampling method for highly imbalanced and overlapped data classification with complex distribution.
Sampling Imbalanced Data with Multi-objective Bilevel Optimization A hybrid sampling method for highly imbalanced and overlapped data classification with complex distribution
Reference 30
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T04:16:11.217114Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation a6789edb-f0f8-4976-80e4-dd1fb5034011 · outbound
This paper cites Scalable Gradient-Based Tuning of Continuous Regularization Hyperparameters.
Sampling Imbalanced Data with Multi-objective Bilevel Optimization Scalable Gradient-Based Tuning of Continuous Regularization Hyperparameters
Reference 31
- Resolution
- verified exact
- local_arxiv, observed 2026-08-07T04:16:10.952977Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 3487696e-cc52-44a6-9ac9-60c3f35371bd · outbound
This paper cites Ctgan-mos: Conditional generative adversarial network based minority-class-augmented oversampling scheme for imbalanced problems.
Sampling Imbalanced Data with Multi-objective Bilevel Optimization Ctgan-mos: Conditional generative adversarial network based minority-class-augmented oversampling scheme for imbalanced problems
Reference 32
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T04:16:11.207022Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 5b0ea9d8-f70a-4bc9-9676-886a3c7df5fb · outbound
This paper cites An Experimental Study With Imbalanced Classification Approaches for Credit Card Fraud Detection.
Sampling Imbalanced Data with Multi-objective Bilevel Optimization An Experimental Study With Imbalanced Classification Approaches for Credit Card Fraud Detection
Reference 33
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T04:16:11.099070Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 2a180182-cf03-40fd-bd0d-36d5a9930f54 · outbound
This paper cites A Bilevel Optimization Framework for Imbalanced Data Classification.
Sampling Imbalanced Data with Multi-objective Bilevel Optimization A Bilevel Optimization Framework for Imbalanced Data Classification
Reference 34
- Resolution
- verified exact
- local_arxiv, observed 2026-08-07T04:16:10.940134Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 4ad66b96-e30b-4f8e-85b3-0fe285bdeb6a · outbound
This paper cites Nguyen, Eric W.
Sampling Imbalanced Data with Multi-objective Bilevel Optimization Nguyen, Eric W
Reference 35
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T04:16:11.090092Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation bbb914f7-7477-4cc4-87eb-cbaceb0376d6 · outbound
This paper cites PyTorch: An Imperative Style, High-Performance Deep Learning Library.
Sampling Imbalanced Data with Multi-objective Bilevel Optimization PyTorch: An Imperative Style, High-Performance Deep Learning Library
Reference 36
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T04:16:10.837373Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 07e01c4b-b3cb-4eac-957f-533ff9bd8f8e · outbound
This paper cites Radius- smote: A new oversampling technique of minority samples based on radius distance for learning from imbalanced data.
Sampling Imbalanced Data with Multi-objective Bilevel Optimization Radius- smote: A new oversampling technique of minority samples based on radius distance for learning from imbalanced data
Reference 37
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T04:16:11.080623Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 22ee78b2-118a-49db-a910-04bc3c430c60 · outbound
This paper cites Handling Imbalanced Classification Problems With Support Vector Machines via Evolutionary Bilevel Optimization.
Sampling Imbalanced Data with Multi-objective Bilevel Optimization Handling Imbalanced Classification Problems With Support Vector Machines via Evolutionary Bilevel Optimization
Reference 38
- Resolution
- verified exact
- local_arxiv, observed 2026-08-07T04:16:10.916286Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 30ed6aa6-ca4c-46de-9a0f-37873b0f37be · outbound
This paper cites SMOTified-GAN for Class Imbal- anced Pattern Classification Problems.
Sampling Imbalanced Data with Multi-objective Bilevel Optimization SMOTified-GAN for Class Imbal- anced Pattern Classification Problems
Reference 39
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T04:16:11.071558Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation e25b754e-2658-4fec-be5a-b2cfdf155342 · outbound
This paper cites Credit Card Fraud Detection under Extreme Imbalanced Data: A Comparative Study of Data-level Algorithms.
Sampling Imbalanced Data with Multi-objective Bilevel Optimization Credit Card Fraud Detection under Extreme Imbalanced Data: A Comparative Study of Data-level Algorithms
Reference 40
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T04:16:11.062855Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 506a4af6-bc02-4d25-bdae-0deed5b63d28 · outbound
This paper cites A multi-objective optimisation approach for class imbalance learning.
Sampling Imbalanced Data with Multi-objective Bilevel Optimization A multi-objective optimisation approach for class imbalance learning
Reference 41
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T04:16:11.053615Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 2cfc3ecf-08dd-4573-ac0c-1045d34a5557 · outbound
This paper cites Toward Robustness in Multi-label Classification: A Data Augmentation Strategy against Imbalance and Noise.
Sampling Imbalanced Data with Multi-objective Bilevel Optimization Toward Robustness in Multi-label Classification: A Data Augmentation Strategy against Imbalance and Noise
Reference 42
- Resolution
- verified exact
- local_arxiv, observed 2026-08-07T04:16:10.902618Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation aaa0572d-4fd2-485f-89b9-b730c47302d1 · outbound
This paper cites A Survey on GAN Techniques for Data Augmentation to Address the Imbalanced Data Issues in Credit Card Fraud Detection.
Sampling Imbalanced Data with Multi-objective Bilevel Optimization A Survey on GAN Techniques for Data Augmentation to Address the Imbalanced Data Issues in Credit Card Fraud Detection
Reference 43
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T04:16:11.043915Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 62d2f5ab-ba11-450e-92bc-f857b30f1662 · outbound
This paper cites IMWMOTE: A novel oversampling technique for fault diagnosis in heterogeneous imbalanced data.
Sampling Imbalanced Data with Multi-objective Bilevel Optimization IMWMOTE: A novel oversampling technique for fault diagnosis in heterogeneous imbalanced data
Reference 44
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T04:16:11.034141Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation bfe68339-7e96-425f-9640-b0babc466374 · outbound
This paper cites A Diversity-Based Synthetic Oversampling Using Clustering for Handling Extreme Imbalance.
Sampling Imbalanced Data with Multi-objective Bilevel Optimization A Diversity-Based Synthetic Oversampling Using Clustering for Handling Extreme Imbalance
Reference 45
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T04:16:11.024402Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation ee6f559a-d498-4e8c-894a-30a136920a9f · outbound
This paper cites Learning from class-imbalanced data using misclassification-focusing generative adversarial networks.
Sampling Imbalanced Data with Multi-objective Bilevel Optimization Learning from class-imbalanced data using misclassification-focusing generative adversarial networks
Reference 46
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T04:16:11.014441Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 6335a690-8fc3-41bb-a25a-d8140352f345 · outbound
This paper cites Theory-Inspired Path-Regularized Differential Network Architecture Search.
Sampling Imbalanced Data with Multi-objective Bilevel Optimization Theory-Inspired Path-Regularized Differential Network Architecture Search
Reference 47
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T04:16:11.004671Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation e150f331-1401-481d-a3b5-232825765ac1 · outbound
This paper cites DARTS: Differentiable Architecture Search.
Sampling Imbalanced Data with Multi-objective Bilevel Optimization DARTS: Differentiable Architecture Search
Reference 2019
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T04:16:10.816744Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 4861b132-7b62-41f0-8eaa-82663f71cf5b · outbound
This paper cites Image-Level or Object-Level? A Tale of Two Resampling Strategies for Long-Tailed Detection.
Sampling Imbalanced Data with Multi-objective Bilevel Optimization Image-Level or Object-Level? A Tale of Two Resampling Strategies for Long-Tailed Detection
Reference 2021
- Resolution
- verified exact
- local_arxiv, observed 2026-08-07T04:16:10.995045Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Pith citing papers
No inbound Pith citation observations are available.