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Paper Citation Record · LEDGER

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

As of 11 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

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T05:50:25.589093Z

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

A source-named dated measurement, never combined with another source.

Source: cited_works

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

Reference 2

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Observation 30507fee-02fc-48a2-8c9b-0da664facb13 · outbound

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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Observation 21dbb1d6-9d28-4d34-bb14-9afb7a8f6666 · outbound

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)

Reference 4

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Observation 984208b2-dd2b-47c2-b2f6-f1cce1512190 · outbound

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)

Reference 5

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Observation 758e864c-0fbb-46d1-bbab-f52acd62b936 · outbound

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)

Reference 6

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Observation df5cb697-80f5-4ecc-8b4b-596b822453a2 · outbound

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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Observation 56371773-5c9e-4789-a6d1-8a5da43a7371 · outbound

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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Observation e0ff6427-eb86-4256-8276-e99e254d7aba · outbound

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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This paper cites In: CIKM.

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

Reference 11

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Observation acc7b526-070c-4ac9-a2c9-af4de9310c47 · outbound

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

Reference 12

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Observation 0ab31b78-75aa-4f31-b8b0-1f13ea79e25a · outbound

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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Observation 06867098-dd50-421f-979b-3b1c39350869 · outbound

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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

Reference 14

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Observation d15ef841-2d1c-401c-ab1f-d8eb9b3ec508 · outbound

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

Reference 15

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

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Observation 77583dbb-3542-434a-b39f-d9bf65ac7e51 · outbound

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

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

Reference 17

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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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Observation 43ccaf1f-3467-4186-9d88-460350098f51 · outbound

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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

Reference 19

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

Reference 20

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

Reference 21

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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

Reference 22

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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)

Reference 23

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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)

Reference 25

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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

Reference 26

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This paper cites In: Proceedings of the AAAI Conference on Artificial Intelligence.

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

Reference 27

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

Reference 28

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

Reference 30

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This paper cites In: International conference on learning representations (2021).

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

Reference 31

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Observation 85cff3ea-1449-4581-b619-460f88eab132 · outbound

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)

Reference 32

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This paper cites In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition.

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

Reference 33

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Observation ce4b360a-fc0e-4cf4-af71-35028b599a9e · outbound

This paper cites Machine Learning109, 1803–1835 (2020).

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

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:50:25.859417Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-07T05:50:25.536317Z digest=sha256:06331cfb32da7a17e0c81bb6ec5b8da3db94d1005d2aeb42f6dbb9e5a5727423

Observation 265cfb35-8811-47ea-881e-52d3691e35b3 · outbound

This paper cites Machine Learning110, 2187–2211 (2021).

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

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:50:25.843504Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-07T05:50:25.540502Z digest=sha256:6da54fae83b22161ce9aba8264f02b0194f88fe95262b12842675f7637894538

Observation 17a1d8f5-256a-4d4d-983e-187032187c40 · outbound

This paper cites Advances in neural information processing systems33, 8101– 8113 (2020).

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

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:50:25.828489Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-07T05:50:25.544761Z digest=sha256:b81220dcddf80a60ef209394ac6f5f2d83b847d4dec1d80d2baa4611dcce74ee

Observation 2789ce1f-6270-4969-afeb-068cda51ac1a · outbound

This paper cites In: Por- tuguese conference on artificial intelligence.

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

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:50:25.813210Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-07T05:50:25.549038Z digest=sha256:c2b43b4db3a1b8074771abc0d1b1dad8b8ed1f28384c3b89637fdeae1933f242

Observation b45ce718-9f42-4d4e-a53a-87570a09e454 · outbound

This paper cites ACM Transactions on Spatial Algorithms and Systems9(1), 1–24 (2023).

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

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:50:25.798600Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-07T05:50:25.553537Z digest=sha256:f122360ec215af578d9df6c12a1dd890aeb1606952b6216428142d2e023a9ed5

Observation 8c2fb6be-6d7a-4393-85ed-a2370ac57320 · outbound

This paper cites Long-tailed Recognition by Routing Diverse Distribution-Aware Experts.

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

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-07T05:50:25.557874Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:50:25.557874Z digest=sha256:cb1fa15f4bd4ea3d1851e5d8936c48d3ed9ccfab9ba7298ffac6fab2f369551b

Observation 87d50673-270e-41a2-b5a9-ad7828083350 · outbound

This paper cites Advances in Neural Information Processing Systems36(2024).

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

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:50:25.783644Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-07T05:50:25.562548Z digest=sha256:194a2c7b88689fc5f8e994b59a06c1b9dba8eb40f9131e62d7a0ab908e9e8d6d

Observation 2f2dc184-65b1-4122-a6d6-60a326cfd9c5 · outbound

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

Resolution
unresolved
no resolver link, observed 2026-08-07T05:50:25.566903Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:50:25.566903Z digest=sha256:7a89a0d354c5a1bd474a6e31f4e7f63e88a4058d0754fac8d1ff07f304fee3cc

Observation 9c5f60ea-fe27-41ef-8fff-8442f826998c · outbound

This paper cites In: International conference on machine learning.

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

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:50:25.760538Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-07T05:50:25.571175Z digest=sha256:0d7bf1777a3a07f4f4cceab2fcdc48c7bf88c809ebe142f1e1e80381920f036e

Observation dec21eaf-34cc-46fe-9311-9b1736edfd46 · outbound

This paper cites an unresolved cited work.

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

Reference 43

Resolution
unresolved
raw_fallback, observed 2026-08-07T05:50:25.745980Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-07T05:50:25.575291Z digest=sha256:628c078fd152ddf25eaaeb2b80c8c640920a1271019cac08500a72de938405ae

Observation e731e8af-5711-4430-b8f5-e83a35b1f681 · outbound

This paper cites Advances in Neural Information Processing Systems33, 11033–11043 (2020).

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

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:50:25.730759Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-07T05:50:25.579506Z digest=sha256:f41839883d394873439361d9623ff93d31ef466bb10eca8ff322d0a337f99aa7

Observation 0303e183-009a-414a-bbaf-2e31244ba30f · outbound

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

Reference 45

Resolution
unresolved
no resolver link, observed 2026-08-07T05:50:25.583797Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:50:25.583797Z digest=sha256:0ba80bc834915240accab44f48b67fb21f8a7a274e0c9d1473dbe9c2b96f4879

Observation 486ac241-8bf7-46cb-a10e-01c1462ba122 · outbound

This paper cites Advances in Neural Information Processing Systems35, 34077–34090 (2022).

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

Reference 46

Resolution
unresolved
no resolver link, observed 2026-08-07T05:50:25.589093Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:50:25.589093Z digest=sha256:8fa36ce1289e021f7c93affc3b6ac76535d85ec4d358478745d46f50cfff99d7

Pith citing papers

No inbound Pith citation observations are available.