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Paper Citation Record · LEDGER

A Model for Imbalanced Label Aggregation: A Focus on Minority-Class Detection

As of 10 August 2026, this Paper Citation Record lists 100 of 159 outbound references and 0 inbound Pith citation observations for arXiv:2607.24622.

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

pith.paper-citation-record.v1
2607.24622 v1

Coverage vector

measured 100 of 159 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-07-31T10:23:29.661956Z

measured 100 of 100 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

100 of 159 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved99
  • parse uncertain1
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 0329bed7-f6c1-4c1a-a41f-1f2dc7e17c5a · outbound

This paper cites , title =.

A Model for Imbalanced Label Aggregation: A Focus on Minority-Class Detection , title =

Reference 1

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source=arxiv_source observed=2026-07-31T10:23:28.645588Z digest=sha256:a453cd1118de140d41347f395c71d7b73a2c47577848b5c20672d836ad03c59e

Observation f1f0b45f-0ef5-450b-b6fe-2032feaf862a · outbound

This paper cites Intelligent Data Analysis , volume =.

A Model for Imbalanced Label Aggregation: A Focus on Minority-Class Detection Intelligent Data Analysis , volume =

Reference 2

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source=arxiv_source observed=2026-07-31T10:23:28.654743Z digest=sha256:24358312d53863a949f2ae15026dd448079e330f3dcc372388cd5fae55c559d8

Observation 4b2d9caa-ea4f-4a9f-aea3-c8ebaec0b9fa · outbound

This paper cites and Jordan, Michael I.

A Model for Imbalanced Label Aggregation: A Focus on Minority-Class Detection and Jordan, Michael I

Reference 3

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source=arxiv_source observed=2026-07-31T10:23:28.674746Z digest=sha256:51ecc73e5fdc7d2ae03a4af76f0007ae6af54432c31d7cb676fb62d9848f2c55

Observation 438e545e-acd6-4ee6-ac17-d5cef7d25335 · outbound

This paper cites , title =.

A Model for Imbalanced Label Aggregation: A Focus on Minority-Class Detection , title =

Reference 4

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source=arxiv_source observed=2026-07-31T10:23:28.724740Z digest=sha256:ec2128d098642388d464f242da6a582e924d6d83e3c438ce64107da961fac730

Observation d85ec8e7-09df-4155-a86b-a09e6bdc096e · outbound

This paper cites an unresolved cited work.

A Model for Imbalanced Label Aggregation: A Focus on Minority-Class Detection Unresolved cited work

Reference 5

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source=arxiv_source observed=2026-07-31T10:23:28.764739Z digest=sha256:3628a9dee501591e60efb992ddbe37c4b4515bf655426aba2c187d1481ddac37

Observation 426c6108-db3c-4d15-bef1-c7e95223fcea · outbound

This paper cites and Laird, Nan M.

A Model for Imbalanced Label Aggregation: A Focus on Minority-Class Detection and Laird, Nan M

Reference 6

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source=arxiv_source observed=2026-07-31T10:23:28.794733Z digest=sha256:8a8b5405de337d553638cdcff363cebf900547721bbc6414e4a3272f314c0ce7

Observation 4221bf1f-d5f8-42e5-af84-f5f61862507d · outbound

This paper cites and Steinhardt, Jacob , title =.

A Model for Imbalanced Label Aggregation: A Focus on Minority-Class Detection and Steinhardt, Jacob , title =

Reference 7

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source=arxiv_source observed=2026-07-31T10:23:28.834738Z digest=sha256:9db496eb9ae75327e383c3b7884ed07579ba61981989fcac79b21a7d88b5be38

Observation 8384ba3b-38bd-4e1d-a13f-b16afb883385 · outbound

This paper cites and Chiang, Mung and Studer, Christoph , title =.

A Model for Imbalanced Label Aggregation: A Focus on Minority-Class Detection and Chiang, Mung and Studer, Christoph , title =

Reference 8

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source=arxiv_source observed=2026-07-31T10:23:28.861923Z digest=sha256:87821f5fea066984a180ced8983e4a18771e1ae82bff4482d872a93be9ce8e67

Observation 135993f4-fcfc-42a6-9f06-407fb9eb98b3 · outbound

This paper cites and Plan, Yaniv and van den Berg, Ewout and Wootters, Mary , title =.

A Model for Imbalanced Label Aggregation: A Focus on Minority-Class Detection and Plan, Yaniv and van den Berg, Ewout and Wootters, Mary , title =

Reference 9

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source=arxiv_source observed=2026-07-31T10:23:28.880021Z digest=sha256:49cdede616865eaec654399b6f1b07c977183d3dc4487cc6e9a7379b4d16df5e

Observation d794d564-374d-4c63-ba5e-56c739d5c097 · outbound

This paper cites , title =.

A Model for Imbalanced Label Aggregation: A Focus on Minority-Class Detection , title =

Reference 10

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source=arxiv_source observed=2026-07-31T10:23:28.904740Z digest=sha256:e12a303251d493b0f10a2f48bf40718e2a5bda8bf979a595f27247892d51ba0a

Observation 9e5f24d4-3b99-4e4d-a36c-3d197576986b · outbound

This paper cites Statistics & Probability Letters , volume =.

A Model for Imbalanced Label Aggregation: A Focus on Minority-Class Detection Statistics & Probability Letters , volume =

Reference 11

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source=arxiv_source observed=2026-07-31T10:23:28.926012Z digest=sha256:4b71462f3782facbc7f7bfa11d98c872cee13945d95836dc0bbd4efe304c8cc5

Observation aadfb5cf-eb63-4613-8c44-d56df287f04f · outbound

This paper cites Haberman , title =.

A Model for Imbalanced Label Aggregation: A Focus on Minority-Class Detection Haberman , title =

Reference 12

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source=arxiv_source observed=2026-07-31T10:23:28.936587Z digest=sha256:2669bb6f21f9057f44c9a7eedfd31d05bd83a99f7475fc0eb5e0c46ff06522f9

Observation 410ceb3d-f7fa-4df2-ab5f-7270241f1f84 · outbound

This paper cites Wainwright and Bin Yu , title =.

A Model for Imbalanced Label Aggregation: A Focus on Minority-Class Detection Wainwright and Bin Yu , title =

Reference 13

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source=arxiv_source observed=2026-07-31T10:23:28.964740Z digest=sha256:f1cca572d88e2ff4c50b50c7cc2bcca8e8e7bc51012442db40e95d7833823aea

Observation 666fb39b-179f-411c-b128-1d8414506bab · outbound

This paper cites 2019 , eprint=.

A Model for Imbalanced Label Aggregation: A Focus on Minority-Class Detection 2019 , eprint=

Reference 14

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source=arxiv_source observed=2026-07-31T10:23:28.981471Z digest=sha256:2ce21d634dd3f40954a765dd1de5b3100541bad67e57d919cf0f7821a99b8d13

Observation efb9c60c-0610-41ff-a440-e64da275cfa1 · outbound

This paper cites 2026 , eprint=.

A Model for Imbalanced Label Aggregation: A Focus on Minority-Class Detection 2026 , eprint=

Reference 15

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source=arxiv_source observed=2026-07-31T10:23:28.991315Z digest=sha256:4bda98395e902e04ec3b537e6953c9fd86e6345f7b55e240503e13020712ef48

Observation 459ee6c0-9536-4848-8bb8-d425d5ecb3c5 · outbound

This paper cites 1997 , publisher=.

A Model for Imbalanced Label Aggregation: A Focus on Minority-Class Detection 1997 , publisher=

Reference 16

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source=arxiv_source observed=2026-07-31T10:23:29.003145Z digest=sha256:9904d326eb1a5b24f192e04367c1bf8b10b1e046ed3386af3b927d73b7c4edd8

Observation b55d74b1-f7e9-4b75-b582-1bee31f3fb57 · outbound

This paper cites 2023 , eprint=.

A Model for Imbalanced Label Aggregation: A Focus on Minority-Class Detection 2023 , eprint=

Reference 17

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source=arxiv_source observed=2026-07-31T10:23:29.012044Z digest=sha256:8559b698293349f5d3f2ab31fba82e557c5d549bfc8ee50f2c98457cac9f0e32

Observation 517330bc-b838-40b6-acdc-0708924882fb · outbound

This paper cites International Conference on Machine Learning , pages=.

A Model for Imbalanced Label Aggregation: A Focus on Minority-Class Detection International Conference on Machine Learning , pages=

Reference 18

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source=arxiv_source observed=2026-07-31T10:23:29.042954Z digest=sha256:1c9a7a95336b658e4ff05aaea6ae4746836e995f3f58210dfc1cc5126d75690d

Observation ec985401-248b-4523-91a7-faa27aeac3b5 · outbound

This paper cites Bayes-Optimal Classifiers under Group Fairness.

A Model for Imbalanced Label Aggregation: A Focus on Minority-Class Detection Bayes-Optimal Classifiers under Group Fairness

Reference 19

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source=arxiv_source observed=2026-07-31T10:23:29.051195Z digest=sha256:d474ed75e89f01b0cc65056abac7ab10dd0b3ea4969aee4905a7eb3b2120df1b

Observation 4de562a0-4c71-4bc2-a41e-617bcb04dd63 · outbound

This paper cites 2022 , eprint=.

A Model for Imbalanced Label Aggregation: A Focus on Minority-Class Detection 2022 , eprint=

Reference 20

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source=arxiv_source observed=2026-07-31T10:23:29.063526Z digest=sha256:741cc315116846968d8596c9ac3bb2364680475d7b160391288a920dde2dc540

Observation 3a1a9fc8-467f-4028-b145-43c9df5efbcb · outbound

This paper cites Proceedings of 2nd Workshop on Diversity in Artificial Intelligence (AIDBEI) , year =.

A Model for Imbalanced Label Aggregation: A Focus on Minority-Class Detection Proceedings of 2nd Workshop on Diversity in Artificial Intelligence (AIDBEI) , year =

Reference 21

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source=arxiv_source observed=2026-07-31T10:23:29.074095Z digest=sha256:f36e4d61a0157ca66caeb22f4fe80f247ced3631d945880698f1d32465317435

Observation 927920e7-edb4-43ba-88c4-6231e04337fd · outbound

This paper cites an unresolved cited work.

A Model for Imbalanced Label Aggregation: A Focus on Minority-Class Detection Unresolved cited work

Reference 22

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source=arxiv_source observed=2026-07-31T10:23:29.081388Z digest=sha256:0e9fc5a46bccf0addb59681a512ecf791d6b81eb5a29142f49d8a5e1164f8322

Observation 1bfa7d52-f093-4998-af75-fb2f7ec129fa · outbound

This paper cites Proceedings of the 23rd acm sigkdd international conference on knowledge discovery and data mining , pages=.

A Model for Imbalanced Label Aggregation: A Focus on Minority-Class Detection Proceedings of the 23rd acm sigkdd international conference on knowledge discovery and data mining , pages=

Reference 23

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source=arxiv_source observed=2026-07-31T10:23:29.087127Z digest=sha256:cae96699f18b0b3677cbfc1924cfed528eb8b000419a5a29bbab2fa9a7dc5c10

Observation f66708ec-edae-4faf-ad8b-9541821d3bbb · outbound

This paper cites Fairness definitions explained , doi =.

A Model for Imbalanced Label Aggregation: A Focus on Minority-Class Detection Fairness definitions explained , doi =

Reference 24

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source=arxiv_source observed=2026-07-31T10:23:29.094080Z digest=sha256:e3c56e208e067c92e47e64aa2d0f842da0f37bf6d5b87d2d5e480c943dd50c4b

Observation be4f1391-d452-4391-bae0-3f30f7a734ce · outbound

This paper cites 2018 , eprint=.

A Model for Imbalanced Label Aggregation: A Focus on Minority-Class Detection 2018 , eprint=

Reference 25

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source=arxiv_source observed=2026-07-31T10:23:29.106659Z digest=sha256:9401e89dffdc70d0c446ffdc26204fe2037e7b23397416406ac38aee83085035

Observation 3967d605-fa8e-4b3a-aca9-019800e92117 · outbound

This paper cites 2025 , eprint=.

A Model for Imbalanced Label Aggregation: A Focus on Minority-Class Detection 2025 , eprint=

Reference 26

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source=arxiv_source observed=2026-07-31T10:23:29.112879Z digest=sha256:a402d473c113a5d8d5526adf3ac576c874ba845c6298877ed459e83bcb1cfb1e

Observation e2c7dac0-9c00-42c2-be8d-d2b3bcad8284 · outbound

This paper cites 2011 , eprint=.

A Model for Imbalanced Label Aggregation: A Focus on Minority-Class Detection 2011 , eprint=

Reference 27

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source=arxiv_source observed=2026-07-31T10:23:29.118520Z digest=sha256:33db31885addfffef5645be48d69e3da9bd63bc8bce87130d10b2c7312b88bcb

Observation 6b6820c7-6857-4135-8a41-0112f28d5eb8 · outbound

This paper cites The distance function and Lipschitz classes of mappings between metric spaces , volume =.

A Model for Imbalanced Label Aggregation: A Focus on Minority-Class Detection The distance function and Lipschitz classes of mappings between metric spaces , volume =

Reference 28

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source=arxiv_source observed=2026-07-31T10:23:29.144373Z digest=sha256:c3bda175d3d2ee0ea79d6792b778ded95494ce268968f0fd80265b5afbcfde2c

Observation 3328aeb8-d47a-4b70-8533-cb3c6ee44c09 · outbound

This paper cites Equality of Opportunity in Supervised Learning.

A Model for Imbalanced Label Aggregation: A Focus on Minority-Class Detection Equality of Opportunity in Supervised Learning

Reference 29

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source=arxiv_source observed=2026-07-31T10:23:29.159775Z digest=sha256:b8c654d619e268f793817b111ab786f2d687a4d1be085d03d1025f37fbfa8c3d

Observation f12daee4-9445-4683-a682-3e5dbd9cdebd · outbound

This paper cites Algorithmic decision making and the cost of fairness.

A Model for Imbalanced Label Aggregation: A Focus on Minority-Class Detection Algorithmic decision making and the cost of fairness

Reference 30

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source=arxiv_source observed=2026-07-31T10:23:29.169651Z digest=sha256:6a84828197076db4f6704b6816cfabf284357f3c37975f1082f45c2708f3aca5

Observation d0f49751-5ae0-4dca-9683-283ca36cc69f · outbound

This paper cites Journal of Machine Learning Research , year =.

A Model for Imbalanced Label Aggregation: A Focus on Minority-Class Detection Journal of Machine Learning Research , year =

Reference 31

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source=arxiv_source observed=2026-07-31T10:23:29.178261Z digest=sha256:af92d947b52b948e7ab6a011038a1e2b2652d82ed7428799ab6ac20644ff4363

Observation e8d1a550-f056-469b-8a9a-09e6b4e0c72d · outbound

This paper cites The Risk of Racial Bias in Hate Speech Detection.

A Model for Imbalanced Label Aggregation: A Focus on Minority-Class Detection The Risk of Racial Bias in Hate Speech Detection

Reference 32

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source=arxiv_source observed=2026-07-31T10:23:29.184433Z digest=sha256:05fd703c4eb78523eefed2ca9453df60f23193ca6d84465120e402c0417ccd26

Observation fb3c1f25-7762-4268-82b1-f9f9bcb24d8d · outbound

This paper cites Consistency of weighted majority votes , volume =.

A Model for Imbalanced Label Aggregation: A Focus on Minority-Class Detection Consistency of weighted majority votes , volume =

Reference 33

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source=arxiv_source observed=2026-07-31T10:23:29.192770Z digest=sha256:1cd103855f1c03e0d14a282c26ca1bb7dbdf0d7b079de58c57bf88e843ad05e4

Observation d3ab4e0c-6dd6-4aa7-b5b4-9ce3afb5ae23 · outbound

This paper cites Advances in Neural Information Processing Systems , volume=.

A Model for Imbalanced Label Aggregation: A Focus on Minority-Class Detection Advances in Neural Information Processing Systems , volume=

Reference 34

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source=arxiv_source observed=2026-07-31T10:23:29.201082Z digest=sha256:21f90d2729477ae5d5219f36a4dee126a84cb3d20eb2f597ff8ada3293b5c809

Observation 2cdd5741-68a1-4469-a185-42cc8a80a935 · outbound

This paper cites Advances in Neural Information Processing Systems , volume=.

A Model for Imbalanced Label Aggregation: A Focus on Minority-Class Detection Advances in Neural Information Processing Systems , volume=

Reference 35

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source=arxiv_source observed=2026-07-31T10:23:29.206550Z digest=sha256:5ca2d4c7991218b55b726a059c5e41bb4ed842de66f17d525cacd4a9a6dac3a5

Observation b55b61c8-adee-4d6d-acdf-46b5ddbe0f88 · outbound

This paper cites World Wide Web Conference , pages=.

A Model for Imbalanced Label Aggregation: A Focus on Minority-Class Detection World Wide Web Conference , pages=

Reference 36

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source=arxiv_source observed=2026-07-31T10:23:29.212296Z digest=sha256:ab774b7ddb485d5ff5dacaaeb996db4eeb093b63282f7d243850c3358e8ad010

Observation 6d83c4cd-160d-487d-bf77-bb3a6e644c93 · outbound

This paper cites International Economic Review , volume=.

A Model for Imbalanced Label Aggregation: A Focus on Minority-Class Detection International Economic Review , volume=

Reference 37

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source=arxiv_source observed=2026-07-31T10:23:29.219137Z digest=sha256:d729343fdc54be5804ce1077ebcd47e4808d74dfe43b332e53a31d05316f7c42

Observation 6e5d5284-d628-4acd-b625-06923f3026ad · outbound

This paper cites Conference on Empirical Methods in Natural Language Processing and the International Joint Conference on Natural Language Processing , pages=.

A Model for Imbalanced Label Aggregation: A Focus on Minority-Class Detection Conference on Empirical Methods in Natural Language Processing and the International Joint Conference on Natural Language Processing , pages=

Reference 38

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source=arxiv_source observed=2026-07-31T10:23:29.227143Z digest=sha256:ffc20e50761fc1656e4bd7d4c8651f43fd1836b94c88aa020036231c34d59bab

Observation 913ba667-bfad-4d51-a3c6-df3b866ee41d · outbound

This paper cites Safe Imitation Learning on Real-Life Highway Data for Human-like Autonomous Driving.

A Model for Imbalanced Label Aggregation: A Focus on Minority-Class Detection Safe Imitation Learning on Real-Life Highway Data for Human-like Autonomous Driving

Reference 39

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source=arxiv_source observed=2026-07-31T10:23:29.232388Z digest=sha256:d9b0acd16493ad98d56b98558d347f0c61d4a14bc5fd36450bf7eba69137860c

Observation 727243ae-e310-4e2a-a603-71e832e593ed · outbound

This paper cites International Conference on Machine Learning , pages =.

A Model for Imbalanced Label Aggregation: A Focus on Minority-Class Detection International Conference on Machine Learning , pages =

Reference 40

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source=arxiv_source observed=2026-07-31T10:23:29.238345Z digest=sha256:6c4512d0b9673457510634dbf235cf29f289d0431414f85c9ac0fdf9ce80a61d

Observation 7187c559-038e-4610-b270-432a5692394a · outbound

This paper cites Advances in Neural Information Processing Systems , volume =.

A Model for Imbalanced Label Aggregation: A Focus on Minority-Class Detection Advances in Neural Information Processing Systems , volume =

Reference 41

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source=arxiv_source observed=2026-07-31T10:23:29.246055Z digest=sha256:ed19f18ef7fc1b9ad676332f07e46c74250510096bccff643ac865d071c4b377

Observation f0119b24-ceff-43d6-b522-18393143fa5b · outbound

This paper cites 2019 , eprint=.

A Model for Imbalanced Label Aggregation: A Focus on Minority-Class Detection 2019 , eprint=

Reference 42

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source=arxiv_source observed=2026-07-31T10:23:29.251723Z digest=sha256:713d0c8f7563724d6548cf53ecee98781907dfeabaf06d9d49d6bef274da5532

Observation 11c302d7-bda6-4839-80c5-357b4134b45b · outbound

This paper cites Learning with Noisy Labels Revisited: A Study on.

A Model for Imbalanced Label Aggregation: A Focus on Minority-Class Detection Learning with Noisy Labels Revisited: A Study on

Reference 43

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source=arxiv_source observed=2026-07-31T10:23:29.258820Z digest=sha256:5b8a237851278459fdcd09b168668cb5eec4af4b044c5d4c0dde3a29bb0b7587

Observation 1170d7ff-a4ec-4b22-86e0-ed6269cc27e9 · outbound

This paper cites Maximum Likelihood Estimation of Observer Error-Rates Using the.

A Model for Imbalanced Label Aggregation: A Focus on Minority-Class Detection Maximum Likelihood Estimation of Observer Error-Rates Using the

Reference 44

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source=arxiv_source observed=2026-07-31T10:23:29.267378Z digest=sha256:d52614f01cfdc80f9ac6d28f673a6eebe266093cabcf56481c960939ded4202d

Observation 0b377aea-a132-47af-9f93-03b9a1e29324 · outbound

This paper cites Civil Engineering and Environmental Systems , volume=.

A Model for Imbalanced Label Aggregation: A Focus on Minority-Class Detection Civil Engineering and Environmental Systems , volume=

Reference 45

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source=arxiv_source observed=2026-07-31T10:23:29.276826Z digest=sha256:6b03ea67564324b0e84af15fa079460846e576ca1070b72dfffb76f2e999bc7b

Observation 560b4601-4084-48bd-8760-e9226e6e14f2 · outbound

This paper cites CROWDLAB: Supervised learning to infer consensus labels and quality scores for data with multiple annotators.

A Model for Imbalanced Label Aggregation: A Focus on Minority-Class Detection CROWDLAB: Supervised learning to infer consensus labels and quality scores for data with multiple annotators

Reference 46

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source=arxiv_source observed=2026-07-31T10:23:29.282500Z digest=sha256:e439e34a17adefd9be53dd81c64edebbc051d4f2f4c5c2c4041e72d5190550cf

Observation 15041903-6c90-4a36-9f20-0cd4687b1e56 · outbound

This paper cites ACM SIGKDD International Conference on Knowledge Discovery & Data Mining , pages=.

A Model for Imbalanced Label Aggregation: A Focus on Minority-Class Detection ACM SIGKDD International Conference on Knowledge Discovery & Data Mining , pages=

Reference 47

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source=arxiv_source observed=2026-07-31T10:23:29.290023Z digest=sha256:6a51f656da01e51bcc5a99cb8a710f5924487affe2ee036874f2fe603e2656e4

Observation d8ffe631-83d6-4c4f-acf2-235eea82d8bc · outbound

This paper cites Test , volume=.

A Model for Imbalanced Label Aggregation: A Focus on Minority-Class Detection Test , volume=

Reference 48

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source=arxiv_source observed=2026-07-31T10:23:29.295376Z digest=sha256:ce59f0238a96f89113bb6a800a87e993a249a554e1161fdd6b90a7271dd1afad

Observation 54c727b1-4b7a-41b7-ae09-d7dbd7dc26a1 · outbound

This paper cites Advances in Neural Information Processing Systems , volume =.

A Model for Imbalanced Label Aggregation: A Focus on Minority-Class Detection Advances in Neural Information Processing Systems , volume =

Reference 50

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source=arxiv_source observed=2026-07-31T10:23:29.311090Z digest=sha256:b8b486811d337b92648f64344ee5ef297c21df971fb6bf4a3d27c9f0d1262179

Observation 8ba011cf-572e-45cc-a9ca-80429b32ad43 · outbound

This paper cites 2023 , school =.

A Model for Imbalanced Label Aggregation: A Focus on Minority-Class Detection 2023 , school =

Reference 51

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source=arxiv_source observed=2026-07-31T10:23:29.318438Z digest=sha256:576544880446b56c1494d3ee88f2b1916483f1d04f1eb7ab5576e60584fa8792

Observation 38e15396-1d9f-49df-ad33-c03e10ce535e · outbound

This paper cites International Conference on Machine Learning , pages =.

A Model for Imbalanced Label Aggregation: A Focus on Minority-Class Detection International Conference on Machine Learning , pages =

Reference 52

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source=arxiv_source observed=2026-07-31T10:23:29.324031Z digest=sha256:b9037420d7cdbcfaf540d17a2dbcb621330d0080e7d08e271099fffacdcae6d3

Observation ae54c502-f3dd-41b2-8a4e-fe4855624f4c · outbound

This paper cites 2018 , publisher=.

A Model for Imbalanced Label Aggregation: A Focus on Minority-Class Detection 2018 , publisher=

Reference 53

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source=arxiv_source observed=2026-07-31T10:23:29.329928Z digest=sha256:0d678aa931526a319bb8db9145607e88269976f7bd2e54d6bd5bc4e7baa7a875

Observation ae821a71-0808-44c8-8e14-f6c69a820eff · outbound

This paper cites International Conference on Machine Learning , pages=.

A Model for Imbalanced Label Aggregation: A Focus on Minority-Class Detection International Conference on Machine Learning , pages=

Reference 54

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source=arxiv_source observed=2026-07-31T10:23:29.338820Z digest=sha256:a61b8b2e352d30516b1eaa62902c6f6398e1093b9c072de613cd08e7564581e2

Observation 3e2bdf24-252b-4400-9cc8-5095f2d9a4ca · outbound

This paper cites 2019 , publisher=.

A Model for Imbalanced Label Aggregation: A Focus on Minority-Class Detection 2019 , publisher=

Reference 55

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source=arxiv_source observed=2026-07-31T10:23:29.353230Z digest=sha256:65f1b7836eff91c2a9aa2856fc55384c7121a3dc09ac0dc784169f89e1e35a80

Observation 521e8315-a8a1-4c1f-869e-59a406171b2b · outbound

This paper cites IEEE Access , volume=.

A Model for Imbalanced Label Aggregation: A Focus on Minority-Class Detection IEEE Access , volume=

Reference 56

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source=arxiv_source observed=2026-07-31T10:23:29.358811Z digest=sha256:301d567350c31e4bab1047beb4611941aac992d6819371f1271d1ece6dab337f

Observation 28ce9e5e-49b6-4f09-b7f1-dd233f5f29f6 · outbound

This paper cites , author =.

A Model for Imbalanced Label Aggregation: A Focus on Minority-Class Detection , author =

Reference 57

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source=arxiv_source observed=2026-07-31T10:23:29.364620Z digest=sha256:7ec55d7c1ad5ceb3c5ec631deeec0d8058a0403a1534fd8dcdebdba1aaca8c97

Observation 5fe5d198-619a-4b3a-9c94-661e62875547 · outbound

This paper cites an unresolved cited work.

A Model for Imbalanced Label Aggregation: A Focus on Minority-Class Detection Unresolved cited work

Reference 58

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source=arxiv_source observed=2026-07-31T10:23:29.370792Z digest=sha256:0de82db3889f8bfe8761c5afa1bffd00894002ed755eb5b7ce4e176fb451bdd8

Observation 18e68693-0ce6-425c-b44c-b1b4b43b9a16 · outbound

This paper cites Knowledge and Information Systems , volume=.

A Model for Imbalanced Label Aggregation: A Focus on Minority-Class Detection Knowledge and Information Systems , volume=

Reference 59

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source=arxiv_source observed=2026-07-31T10:23:29.376651Z digest=sha256:a46220313dcd534e044a311ceeb374c57ab0f942545e20acf8abf9a99904aaf4

Observation cf5052d3-aae9-421b-881d-26a765d2154d · outbound

This paper cites Science advances , volume=.

A Model for Imbalanced Label Aggregation: A Focus on Minority-Class Detection Science advances , volume=

Reference 60

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source=arxiv_source observed=2026-07-31T10:23:29.382296Z digest=sha256:8a59cce459bfaa21eb8fe96b83778462bd6daa035aeb5edd78912e7cccf124a8

Observation 0032d7fb-db3e-4b94-be88-5924ed96c361 · outbound

This paper cites AAAI/ACM Conference on AI, Ethics, and Society , pages=.

A Model for Imbalanced Label Aggregation: A Focus on Minority-Class Detection AAAI/ACM Conference on AI, Ethics, and Society , pages=

Reference 61

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source=arxiv_source observed=2026-07-31T10:23:29.387103Z digest=sha256:8b8b44a579fed5b9754757b9cc9adadb15b3099253cf9c4ff6ec38f762951c11

Observation 7a678a92-82c2-4fed-9915-326166d825d5 · outbound

This paper cites Joint European Conference on Machine Learning and Knowledge Discovery in Databases , pages =.

A Model for Imbalanced Label Aggregation: A Focus on Minority-Class Detection Joint European Conference on Machine Learning and Knowledge Discovery in Databases , pages =

Reference 62

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source=arxiv_source observed=2026-07-31T10:23:29.392887Z digest=sha256:8312693ed5d0a65b7b7f053463f3b02b4ef931bdeedb69010147091e58dac3f8

Observation f8b87b3a-97be-465e-be5c-5c0551729432 · outbound

This paper cites Learning to Complement Humans.

A Model for Imbalanced Label Aggregation: A Focus on Minority-Class Detection Learning to Complement Humans

Reference 63

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source=arxiv_source observed=2026-07-31T10:23:29.400322Z digest=sha256:cbafb4ff6fb3ebae82f74e2cb3aa3f96577ee48996ded951ce1bf68f23dd8323

Observation dc3d2098-257e-40ef-9722-a45249c9b635 · outbound

This paper cites Conference on Causal Learning and Reasoning , pages =.

A Model for Imbalanced Label Aggregation: A Focus on Minority-Class Detection Conference on Causal Learning and Reasoning , pages =

Reference 64

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source=arxiv_source observed=2026-07-31T10:23:29.416646Z digest=sha256:544adfe596d8eb14d9a8048f231226524c94b0b053319d11700d6e8efe10cb0a

Observation c0276a8b-cea5-4b77-9f33-147518d56e31 · outbound

This paper cites Pattern Recognition , pages =.

A Model for Imbalanced Label Aggregation: A Focus on Minority-Class Detection Pattern Recognition , pages =

Reference 65

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source=arxiv_source observed=2026-07-31T10:23:29.425747Z digest=sha256:da273f279908156311eaddfa1f37bd6b565a0ccb7860110e83114bbc0c816f7f

Observation d1a824f9-5eab-4d88-a825-58ac26fe66e3 · outbound

This paper cites 2021 , eprint=.

A Model for Imbalanced Label Aggregation: A Focus on Minority-Class Detection 2021 , eprint=

Reference 66

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source=arxiv_source observed=2026-07-31T10:23:29.433928Z digest=sha256:78247ca855a6b5e7a417268ce7f370850c735fa60d0a6e8c2521bdee0fa51c44

Observation 0d59013a-7154-498b-b58c-30ae399c11c6 · outbound

This paper cites Classification in the Presence of Label Noise: A Survey , year=.

A Model for Imbalanced Label Aggregation: A Focus on Minority-Class Detection Classification in the Presence of Label Noise: A Survey , year=

Reference 67

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source=arxiv_source observed=2026-07-31T10:23:29.441427Z digest=sha256:46201974ff83b29b15f52c58699157c96d3b880659d1cbadf05df1ff24d8dc88

Observation 6d1efa75-efa5-46d2-941d-c289019c3664 · outbound

This paper cites ACM SIGKDD Conference on Knowledge Discovery and Data Mining , pages=.

A Model for Imbalanced Label Aggregation: A Focus on Minority-Class Detection ACM SIGKDD Conference on Knowledge Discovery and Data Mining , pages=

Reference 68

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source=arxiv_source observed=2026-07-31T10:23:29.446916Z digest=sha256:397038f84eab2ad9d5b53033b50ba4ca48df1b5c0fe07f25b4ba5b44d1e442f9

Observation 63fd0a65-e266-41df-8cac-c8c4e11037bb · outbound

This paper cites and Cogswell, Michael and Das, Abhishek and Vedantam, Ramakrishna and Parikh, Devi and Batra, Dhruv , year=.

A Model for Imbalanced Label Aggregation: A Focus on Minority-Class Detection and Cogswell, Michael and Das, Abhishek and Vedantam, Ramakrishna and Parikh, Devi and Batra, Dhruv , year=

Reference 69

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source=arxiv_source observed=2026-07-31T10:23:29.454032Z digest=sha256:d4dd91e6667d417b4bee5348a0b0f330d5992f1be11026285c6f7d55caf90ec5

Observation 739f7959-de39-446e-8e58-147d7a0f0afc · outbound

This paper cites Raykar and Shipeng Yu and Linda H.

A Model for Imbalanced Label Aggregation: A Focus on Minority-Class Detection Raykar and Shipeng Yu and Linda H

Reference 70

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source=arxiv_source observed=2026-07-31T10:23:29.461127Z digest=sha256:093cf0a31c8871f3b1472e6de5f4edb738117d8cd0e9522cd3d21bd647d1c938

Observation 94d11144-e5b6-43a0-8a66-e8e568a5ce8b · outbound

This paper cites 5th International Conference on Learning Representations , year =.

A Model for Imbalanced Label Aggregation: A Focus on Minority-Class Detection 5th International Conference on Learning Representations , year =

Reference 71

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source=arxiv_source observed=2026-07-31T10:23:29.466975Z digest=sha256:a44497c269a7f383959a4b38313fa9fbc21340fd1c9cf8e45633206d43261160

Observation a8e61d6f-1452-4e64-a43c-7adb8f4e6294 · outbound

This paper cites Using Boosting to Detect Noisy Data.

A Model for Imbalanced Label Aggregation: A Focus on Minority-Class Detection Using Boosting to Detect Noisy Data

Reference 72

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source=arxiv_source observed=2026-07-31T10:23:29.472010Z digest=sha256:17f8b877f75216fcfc9a7e879bdf6a57d703a906551e3905138d793490e476d8

Observation 1ccd8710-e666-4a31-9ac0-c92530ef82c6 · outbound

This paper cites Machine Learning , year=.

A Model for Imbalanced Label Aggregation: A Focus on Minority-Class Detection Machine Learning , year=

Reference 73

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source=arxiv_source observed=2026-07-31T10:23:29.478950Z digest=sha256:ff3f27ffbe55cc77271dcfd3e266ad4fef438ba5f95a6afb7d1b0d5de24761ff

Observation 7800aae0-9ef2-4069-8030-b66ccb1fb6f0 · outbound

This paper cites 2022 , eprint=.

A Model for Imbalanced Label Aggregation: A Focus on Minority-Class Detection 2022 , eprint=

Reference 74

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source=arxiv_source observed=2026-07-31T10:23:29.485582Z digest=sha256:c74a1565d75ad6bd6680a74f26c0521a72d9655d952960bc182890a6726fab60

Observation 107234a4-bcd9-4f15-8297-c6111be34213 · outbound

This paper cites Advances in Neural Information Processing Systems 30 (NeurIPS 2017) , pages =.

A Model for Imbalanced Label Aggregation: A Focus on Minority-Class Detection Advances in Neural Information Processing Systems 30 (NeurIPS 2017) , pages =

Reference 75

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source=arxiv_source observed=2026-07-31T10:23:29.491885Z digest=sha256:d21ab62f76339cd8bdf406f98dd226f8a04dc42b626c3f8e8b262b6b8e00ddf1

Observation 3e4eb664-20a8-4938-b3e6-d1705ac281df · outbound

This paper cites MentorNet: Learning Data-Driven Curriculum for Very Deep Neural Networks on Corrupted Labels , booktitle =.

A Model for Imbalanced Label Aggregation: A Focus on Minority-Class Detection MentorNet: Learning Data-Driven Curriculum for Very Deep Neural Networks on Corrupted Labels , booktitle =

Reference 76

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source=arxiv_source observed=2026-07-31T10:23:29.496780Z digest=sha256:f4c30e31bcdee783ec4edf714ce5e15a15bf6b292a1405f2240da1eb42169e13

Observation e57f172e-355b-4e5d-9e3b-95e223891174 · outbound

This paper cites Tsang and Masashi Sugiyama , title =.

A Model for Imbalanced Label Aggregation: A Focus on Minority-Class Detection Tsang and Masashi Sugiyama , title =

Reference 77

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source=arxiv_source observed=2026-07-31T10:23:29.502748Z digest=sha256:70d18c016f672a93b1510aad4d26e0865c0fa57645a32340c502f6ceca7bb22c

Observation 85dd4415-e2ea-441d-b1aa-ca1431535480 · outbound

This paper cites an unresolved cited work.

A Model for Imbalanced Label Aggregation: A Focus on Minority-Class Detection Unresolved cited work

Reference 78

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source=arxiv_source observed=2026-07-31T10:23:29.509374Z digest=sha256:db99562e6b94904df71a8196fd885ee5049a650c0438814eab116e6cf053d29f

Observation 0d6020c1-3643-4b90-9bd9-85fa1a7dcc05 · outbound

This paper cites Advances in Neural Information Processing Systems (NeurIPS) , pages =.

A Model for Imbalanced Label Aggregation: A Focus on Minority-Class Detection Advances in Neural Information Processing Systems (NeurIPS) , pages =

Reference 79

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source=arxiv_source observed=2026-07-31T10:23:29.516494Z digest=sha256:366fff7752e28020cad44f704d976458bde039342a71dc2deebe63a45af866e3

Observation f19feb56-5b07-4907-b826-74c520bb7605 · outbound

This paper cites Conference on Empirical Methods in Natural Language Processing , pages=.

A Model for Imbalanced Label Aggregation: A Focus on Minority-Class Detection Conference on Empirical Methods in Natural Language Processing , pages=

Reference 80

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source=arxiv_source observed=2026-07-31T10:23:29.522318Z digest=sha256:841cc21da6b54ece7117332916d0b29974ef59c139c3e8b8791ccf6911d855c5

Observation 7a524262-7c58-4a54-8ce5-b7aaf434c229 · outbound

This paper cites IEEE International Conference on Computer Vision , pages =.

A Model for Imbalanced Label Aggregation: A Focus on Minority-Class Detection IEEE International Conference on Computer Vision , pages =

Reference 81

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source=arxiv_source observed=2026-07-31T10:23:29.528383Z digest=sha256:77ff3e9a1e4ac330fcdba5e5bf9621f168f5d39ca63b00a8115c86b8de5dc4a7

Observation a735eafc-9c31-48ab-8622-7cbc44a7a999 · outbound

This paper cites 2015 , eprint=.

A Model for Imbalanced Label Aggregation: A Focus on Minority-Class Detection 2015 , eprint=

Reference 82

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Source-reported events for the cited work

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source=arxiv_source observed=2026-07-31T10:23:29.533092Z digest=sha256:81168a8eb1b95ae20bcbee31c6794e031ffa5e307b8b87e8d25420df46673834

Observation 41707c6c-7bf1-4099-b5d1-e71272478215 · outbound

This paper cites Tsang and Ya Zhang and Masashi Sugiyama , title =.

A Model for Imbalanced Label Aggregation: A Focus on Minority-Class Detection Tsang and Ya Zhang and Masashi Sugiyama , title =

Reference 83

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no resolver link, observed 2026-07-31T10:23:29.538377Z

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source=arxiv_source observed=2026-07-31T10:23:29.538377Z digest=sha256:f78abde81954585e4e9819e68e9ef18574d3d56502a70843c0de5cb1f7102ddc

Observation b6970399-1237-4f50-8fef-aa925070640d · outbound

This paper cites 2019 , eprint=.

A Model for Imbalanced Label Aggregation: A Focus on Minority-Class Detection 2019 , eprint=

Reference 84

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Source-reported events for the cited work

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source=arxiv_source observed=2026-07-31T10:23:29.545733Z digest=sha256:805176c258b699153bcc4bf49812a12a20739ac2e6010ee1fefdf588217daf10

Observation 6f6d5773-a940-40df-b3a8-f6f53ccfe411 · outbound

This paper cites Advances in Neural Information Processing Systems (NeurIPS) , pages =.

A Model for Imbalanced Label Aggregation: A Focus on Minority-Class Detection Advances in Neural Information Processing Systems (NeurIPS) , pages =

Reference 85

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source=arxiv_source observed=2026-07-31T10:23:29.552735Z digest=sha256:943032a6a1466b2a97b922cdbb0e0a4117250c47a0290e8c3c5b7d06d2eecadc

Observation fcd00cab-7394-439f-8226-e73e04b2ee5a · outbound

This paper cites an unresolved cited work.

A Model for Imbalanced Label Aggregation: A Focus on Minority-Class Detection Unresolved cited work

Reference 86

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source=arxiv_source observed=2026-07-31T10:23:29.562911Z digest=sha256:fd469122003048ec00a95223c3c06415e866c58491ad3e1c59629bbf711154af

Observation fe82d7c9-e3f2-4153-acb9-3af74aa35cb4 · outbound

This paper cites CVPR , year=.

A Model for Imbalanced Label Aggregation: A Focus on Minority-Class Detection CVPR , year=

Reference 87

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source=arxiv_source observed=2026-07-31T10:23:29.572946Z digest=sha256:ed7b29c9f78c4b1bc33bd477a5b8e7960db4656b0c085f20cfa2a622cf38bc45

Observation 8f05e433-09bb-4c5a-8f82-6fcea93344ef · outbound

This paper cites an unresolved cited work.

A Model for Imbalanced Label Aggregation: A Focus on Minority-Class Detection Unresolved cited work

Reference 88

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source=arxiv_source observed=2026-07-31T10:23:29.577762Z digest=sha256:c173f528ce88e4d11ff4bc18533e4cc8593cef47ae356110ced37bb09823f972

Observation 17b09587-1281-4486-bf5c-c403c3462f54 · outbound

This paper cites International Conference on Learning Representations , year =.

A Model for Imbalanced Label Aggregation: A Focus on Minority-Class Detection International Conference on Learning Representations , year =

Reference 89

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source=arxiv_source observed=2026-07-31T10:23:29.584698Z digest=sha256:ec8f7e683ce705ade51873a7c7183f1231858c9ceb2c833aed4b29bc6d74fed3

Observation d6ea611f-c8c1-4ee3-a668-56880a02db9b · outbound

This paper cites IEEE Conference on Computer Vision and Pattern Recognition , pages =.

A Model for Imbalanced Label Aggregation: A Focus on Minority-Class Detection IEEE Conference on Computer Vision and Pattern Recognition , pages =

Reference 90

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source=arxiv_source observed=2026-07-31T10:23:29.593557Z digest=sha256:dc60b4dc7df3e8e3db49fcd1c17ae258e88bb1b33e2d804d7c9843e7b9f57a08

Observation 689c0b03-00ee-4710-a29e-15ec3f6b73fa · outbound

This paper cites an unresolved cited work.

A Model for Imbalanced Label Aggregation: A Focus on Minority-Class Detection Unresolved cited work

Reference 91

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source=arxiv_source observed=2026-07-31T10:23:29.598710Z digest=sha256:a1fcc3bfbc23d3287057df1e208073c39e0c5b2872177d8965f1b9ca5b23c64f

Observation a4d10d44-becb-4211-b491-46860cce75f8 · outbound

This paper cites an unresolved cited work.

A Model for Imbalanced Label Aggregation: A Focus on Minority-Class Detection Unresolved cited work

Reference 92

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source=arxiv_source observed=2026-07-31T10:23:29.604546Z digest=sha256:7cfef93837cb97d2670ef1e20113b08309544e910006994a1d1837f6904e4df8

Observation c80fc8f2-81ec-4c88-8738-5749a72fbb63 · outbound

This paper cites an unresolved cited work.

A Model for Imbalanced Label Aggregation: A Focus on Minority-Class Detection Unresolved cited work

Reference 93

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source=arxiv_source observed=2026-07-31T10:23:29.614745Z digest=sha256:a42d5264b1fe9794e59ad8403af8b8464645f3b4a2905adb82a321d9db4e8717

Observation 955409c4-261a-40e3-9884-43639e9fc3e4 · outbound

This paper cites Proceedings of the IEEE , volume =.

A Model for Imbalanced Label Aggregation: A Focus on Minority-Class Detection Proceedings of the IEEE , volume =

Reference 94

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source=arxiv_source observed=2026-07-31T10:23:29.621643Z digest=sha256:b18a4be10c597f1ad05d58d9bc4b8c82647b7762be9f1c081c889b53558ef05f

Observation 84a2ec1c-d148-42e4-b08d-5248bdba6af9 · outbound

This paper cites an unresolved cited work.

A Model for Imbalanced Label Aggregation: A Focus on Minority-Class Detection Unresolved cited work

Reference 95

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source=arxiv_source observed=2026-07-31T10:23:29.630442Z digest=sha256:5f03c12a525df3c2aa1d83c032e57d8bcb1507a1b148de129125c74d4f5997e2

Observation 397a31a7-a176-4c24-922c-2de96101d8bc · outbound

This paper cites NIPS Workshop on Deep Learning and Unsupervised Feature Learning , year =.

A Model for Imbalanced Label Aggregation: A Focus on Minority-Class Detection NIPS Workshop on Deep Learning and Unsupervised Feature Learning , year =

Reference 96

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source=arxiv_source observed=2026-07-31T10:23:29.636894Z digest=sha256:cb5e02dc52bb90138a5ee95eed7e6e998f67bb00f668578a2382b5943e27cb0b

Observation 8be690c9-67d4-434e-9f93-be59c11eb0ad · outbound

This paper cites an unresolved cited work.

A Model for Imbalanced Label Aggregation: A Focus on Minority-Class Detection Unresolved cited work

Reference 97

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source=arxiv_source observed=2026-07-31T10:23:29.642409Z digest=sha256:f578b7636f57b10b6ef062b0628a32696ae026068784570ef8ae38230e9b4867

Observation 669081c8-1563-4e3b-bedd-8dc61074f48f · outbound

This paper cites 2021 , eprint=.

A Model for Imbalanced Label Aggregation: A Focus on Minority-Class Detection 2021 , eprint=

Reference 98

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source=arxiv_source observed=2026-07-31T10:23:29.647305Z digest=sha256:2150cfc3a646d780ba8b413b0f874571a1cdaaa71796a7f11ab43e3d914e41aa

Observation 93959415-d8c5-4760-ba4a-88689abf6188 · outbound

This paper cites A Sharp Uniform Bound for the Distribution of Sums of Bernoulli Trials , volume=.

A Model for Imbalanced Label Aggregation: A Focus on Minority-Class Detection A Sharp Uniform Bound for the Distribution of Sums of Bernoulli Trials , volume=

Reference 99

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source=arxiv_source observed=2026-07-31T10:23:29.651777Z digest=sha256:7851109dc34f5b3892e0b99f475d35207a22559b796a257e8dbfa78f65b4c671

Observation 2653cb64-d7a2-48a2-a17f-c2e42581a481 · outbound

This paper cites Journal of Inequalities and Applications , year=.

A Model for Imbalanced Label Aggregation: A Focus on Minority-Class Detection Journal of Inequalities and Applications , year=

Reference 100

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source=arxiv_source observed=2026-07-31T10:23:29.657062Z digest=sha256:ab69a352aff96667627745e0cc232540d38e68c667d83c160da35943a87a1efd

Observation f054333c-ca2f-49cc-a8ab-6dbb04a2d88c · outbound

This paper cites Proceedings of ICEET , year =.

A Model for Imbalanced Label Aggregation: A Focus on Minority-Class Detection Proceedings of ICEET , year =

Reference 101

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source=arxiv_source observed=2026-07-31T10:23:29.661956Z digest=sha256:f2e69ab401e0db3e4a9dcb4d43872c91fe735193a49865af0d05d9045cc931ad

Pith citing papers

No inbound Pith citation observations are available.