Paper Citation Record · LEDGER

Mixture Experts with Test-Time Self-Supervised Aggregation for Tabular Imbalanced Regression

As of 8 August 2026, this Paper Citation Record lists 46 of 46 outbound references and 0 inbound Pith citation observations for arXiv:2506.07033.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2506.07033 v1

Coverage vector

measured 46 of 46 reference resolution

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measured 46 of 46 standing notices

One-hop event checks from named stored sources.

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measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

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measured 0 of 1 external citation measurements

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Reference resolution

46 of 46 outbound references displayed

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External citation measurements

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Outbound references

Observation a4676dfb-9592-476a-a410-1bce62e99d3c · outbound

This paper cites Electronics11(4), 662 (2022).

Mixture Experts with Test-Time Self-Supervised Aggregation for Tabular Imbalanced Regression Electronics11(4), 662 (2022)

Reference 1

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This paper cites In: Pro- ceedings of the AAAI conference on artificial intelligence.

Mixture Experts with Test-Time Self-Supervised Aggregation for Tabular Imbalanced Regression In: Pro- ceedings of the AAAI conference on artificial intelligence

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This paper cites In: First international workshop on learning with imbalanced domains: Theory and applications.

Mixture Experts with Test-Time Self-Supervised Aggregation for Tabular Imbalanced Regression In: First international workshop on learning with imbalanced domains: Theory and applications

Reference 3

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This paper cites In: Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV).

Mixture Experts with Test-Time Self-Supervised Aggregation for Tabular Imbalanced Regression In: Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV)

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This paper cites Advances in neural information process- ing systems32(2019).

Mixture Experts with Test-Time Self-Supervised Aggregation for Tabular Imbalanced Regression Advances in neural information process- ing systems32(2019)

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This paper cites Journal of artificial intelligence research16, 321– 357 (2002).

Mixture Experts with Test-Time Self-Supervised Aggregation for Tabular Imbalanced Regression Journal of artificial intelligence research16, 321– 357 (2002)

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This paper cites Knowledge-Based Systems252, 109393 (2022).

Mixture Experts with Test-Time Self-Supervised Aggregation for Tabular Imbalanced Regression Knowledge-Based Systems252, 109393 (2022)

Reference 7

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This paper cites In: Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23–28, 2020, Proceedings, Part XXIX 16.

Mixture Experts with Test-Time Self-Supervised Aggregation for Tabular Imbalanced Regression In: Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23–28, 2020, Proceedings, Part XXIX 16

Reference 8

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This paper cites In: Proceedings of the IEEE/CVF conference on com- puter vision and pattern recognition.

Mixture Experts with Test-Time Self-Supervised Aggregation for Tabular Imbalanced Regression In: Proceedings of the IEEE/CVF conference on com- puter vision and pattern recognition

Reference 9

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This paper cites IEEE transactions on pattern analysis and machine intelligence 41(6), 1367–1381 (2018).

Mixture Experts with Test-Time Self-Supervised Aggregation for Tabular Imbalanced Regression IEEE transactions on pattern analysis and machine intelligence 41(6), 1367–1381 (2018)

Reference 10

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Mixture Experts with Test-Time Self-Supervised Aggregation for Tabular Imbalanced Regression In: CIKM

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This paper cites UCI Machine Learning Repository (2013), DOI: https://doi.org/10.24432/C5W894.

Mixture Experts with Test-Time Self-Supervised Aggregation for Tabular Imbalanced Regression UCI Machine Learning Repository (2013), DOI: https://doi.org/10.24432/C5W894

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This paper cites Advances in Neural Information Processing Systems36(2024) Test-Time Aggregated Experts for Tabular Imbalanced Regression 15.

Mixture Experts with Test-Time Self-Supervised Aggregation for Tabular Imbalanced Regression Advances in Neural Information Processing Systems36(2024) Test-Time Aggregated Experts for Tabular Imbalanced Regression 15

Reference 13

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Mixture Experts with Test-Time Self-Supervised Aggregation for Tabular Imbalanced Regression In: Proceedings of the IEEE/CVF Con- ference on Computer Vision and Pattern Recognition

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This paper cites Large Language Model based Multi-Agents: A Survey of Progress and Challenges.

Mixture Experts with Test-Time Self-Supervised Aggregation for Tabular Imbalanced Regression Large Language Model based Multi-Agents: A Survey of Progress and Challenges

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Mixture Experts with Test-Time Self-Supervised Aggregation for Tabular Imbalanced Regression In: Proceedings of the IEEE/CVF conference on computer vision and pattern recognition

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Mixture Experts with Test-Time Self-Supervised Aggregation for Tabular Imbalanced Regression In: Proceedings of the IEEE conference on computer vision and pattern recognition

Reference 18

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Mixture Experts with Test-Time Self-Supervised Aggregation for Tabular Imbalanced Regression In: Proceedings of the IEEE/CVF conference on computer vision and pattern recognition

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Mixture Experts with Test-Time Self-Supervised Aggregation for Tabular Imbalanced Regression Mixtral of Experts

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Mixture Experts with Test-Time Self-Supervised Aggregation for Tabular Imbalanced Regression Decoupling Representation and Classifier for Long-Tailed Recognition

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Mixture Experts with Test-Time Self-Supervised Aggregation for Tabular Imbalanced Regression In: Proceedings of the IEEE/CVF conference on computer vision and pattern recognition

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This paper cites Sociological methods & research33(2), 188–229 (2004).

Mixture Experts with Test-Time Self-Supervised Aggregation for Tabular Imbalanced Regression Sociological methods & research33(2), 188–229 (2004)

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This paper cites International Jour- nal of Data Science and Analytics12(2), 165–174 (2021).

Mixture Experts with Test-Time Self-Supervised Aggregation for Tabular Imbalanced Regression International Jour- nal of Data Science and Analytics12(2), 165–174 (2021)

Reference 24

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Mixture Experts with Test-Time Self-Supervised Aggregation for Tabular Imbalanced Regression In: PKDD (4)

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Mixture Experts with Test-Time Self-Supervised Aggregation for Tabular Imbalanced Regression In: Proceedings of the IEEE/CVF Conference on Computer Vi- sion and Pattern Recognition

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Mixture Experts with Test-Time Self-Supervised Aggregation for Tabular Imbalanced Regression In: Proceedings of the AAAI Conference on Artificial Intelligence

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Mixture Experts with Test-Time Self-Supervised Aggregation for Tabular Imbalanced Regression Long-tail learning via logit adjustment

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Mixture Experts with Test-Time Self-Supervised Aggregation for Tabular Imbalanced Regression In: Proceedings 16 Y.-C

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Mixture Experts with Test-Time Self-Supervised Aggregation for Tabular Imbalanced Regression In: International conference on learning representations (2021)

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This paper cites Advances in neural information processing systems33, 4175–4186 (2020).

Mixture Experts with Test-Time Self-Supervised Aggregation for Tabular Imbalanced Regression Advances in neural information processing systems33, 4175–4186 (2020)

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Mixture Experts with Test-Time Self-Supervised Aggregation for Tabular Imbalanced Regression In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition

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Mixture Experts with Test-Time Self-Supervised Aggregation for Tabular Imbalanced Regression Machine Learning109, 1803–1835 (2020)

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Mixture Experts with Test-Time Self-Supervised Aggregation for Tabular Imbalanced Regression Machine Learning110, 2187–2211 (2021)

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Mixture Experts with Test-Time Self-Supervised Aggregation for Tabular Imbalanced Regression Advances in neural information processing systems33, 8101– 8113 (2020)

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Mixture Experts with Test-Time Self-Supervised Aggregation for Tabular Imbalanced Regression In: Por- tuguese conference on artificial intelligence

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Mixture Experts with Test-Time Self-Supervised Aggregation for Tabular Imbalanced Regression ACM Transactions on Spatial Algorithms and Systems9(1), 1–24 (2023)

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Mixture Experts with Test-Time Self-Supervised Aggregation for Tabular Imbalanced Regression Long-tailed Recognition by Routing Diverse Distribution-Aware Experts

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Mixture Experts with Test-Time Self-Supervised Aggregation for Tabular Imbalanced Regression Advances in Neural Information Processing Systems36(2024)

Reference 40

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This paper cites In: Computer vision–ECCV 2016: 14th European conference, amsterdam, the netherlands, October 11–14, 2016, proceedings, part VII 14.

Mixture Experts with Test-Time Self-Supervised Aggregation for Tabular Imbalanced Regression In: Computer vision–ECCV 2016: 14th European conference, amsterdam, the netherlands, October 11–14, 2016, proceedings, part VII 14

Reference 41

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Mixture Experts with Test-Time Self-Supervised Aggregation for Tabular Imbalanced Regression In: International conference on machine learning

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Mixture Experts with Test-Time Self-Supervised Aggregation for Tabular Imbalanced Regression Advances in Neural Information Processing Systems33, 11033–11043 (2020)

Reference 44

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This paper cites Improving Deep Regression with Ordinal Entropy.

Mixture Experts with Test-Time Self-Supervised Aggregation for Tabular Imbalanced Regression Improving Deep Regression with Ordinal Entropy

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Mixture Experts with Test-Time Self-Supervised Aggregation for Tabular Imbalanced Regression Advances in Neural Information Processing Systems35, 34077–34090 (2022)

Reference 46

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Pith citing papers

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