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Paper Citation Record · LEDGER

Bias-Aware Mislabeling Detection via Decoupled Confident Learning

As of 14 August 2026, this Paper Citation Record lists 95 of 95 outbound references and 0 inbound Pith citation observations for arXiv:2507.07216.

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

pith.paper-citation-record.v1
2507.07216 v2

Coverage vector

measured 95 of 95 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T18:50:59.720869Z

measured 95 of 95 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+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

95 of 95 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation fdda6130-3b4d-4e6b-9fe2-bdeec25fa7c1 · outbound

This paper cites Pathways for design research on artificial intelligence.

Bias-Aware Mislabeling Detection via Decoupled Confident Learning Pathways for design research on artificial intelligence

Reference 1

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Unavailable: canonical work link unavailable.

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Observation c08409a0-600c-4a0e-9eaa-4d22c7ddc23f · outbound

This paper cites How management users view information systems.

Bias-Aware Mislabeling Detection via Decoupled Confident Learning How management users view information systems

Reference 2

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Observation 87be7181-9a2c-47a8-bef9-1cb5d9870d0d · outbound

This paper cites Big data, data science, and analytics: The opportunity and challenge for is research.

Bias-Aware Mislabeling Detection via Decoupled Confident Learning Big data, data science, and analytics: The opportunity and challenge for is research

Reference 3

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Observation 71449443-ced2-4fd6-8e1c-be929afb7ef7 · outbound

This paper cites The effect of differential victim crime reporting on predictive policing systems.

Bias-Aware Mislabeling Detection via Decoupled Confident Learning The effect of differential victim crime reporting on predictive policing systems

Reference 4

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Observation 9aecac9c-1c41-489c-9334-dd235bf1af81 · outbound

This paper cites Learning from noisy examples.

Bias-Aware Mislabeling Detection via Decoupled Confident Learning Learning from noisy examples

Reference 5

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Observation 314bd3ea-7e4b-4dee-94ce-5cc9d38e058c · outbound

This paper cites Managing data quality risk in accounting information systems.

Bias-Aware Mislabeling Detection via Decoupled Confident Learning Managing data quality risk in accounting information systems

Reference 6

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Unavailable: canonical work link unavailable.

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Observation 07bdee38-6784-4094-98be-cbae91041791 · outbound

This paper cites Modeling data and process quality in multi-input, multi-output information systems.

Bias-Aware Mislabeling Detection via Decoupled Confident Learning Modeling data and process quality in multi-input, multi-output information systems

Reference 7

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Unavailable: canonical work link unavailable.

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Observation 9e08af66-289d-48de-a9a8-ad874bb4f35c · outbound

This paper cites Big data’s disparate impact.

Bias-Aware Mislabeling Detection via Decoupled Confident Learning Big data’s disparate impact

Reference 8

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Observation 7a7a4969-2300-424c-9ffa-3076af674e47 · outbound

This paper cites Active label cleaning for improved dataset quality under resource constraints.Nat.

Bias-Aware Mislabeling Detection via Decoupled Confident Learning Active label cleaning for improved dataset quality under resource constraints.Nat

Reference 9

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Observation b8bd7947-509f-44ab-9498-ed77851b429c · outbound

This paper cites Machine learning in healthcare: Fairness, issues, and challenges.

Bias-Aware Mislabeling Detection via Decoupled Confident Learning Machine learning in healthcare: Fairness, issues, and challenges

Reference 10

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Observation ed1d5272-c6d0-452d-9876-2008382da5c8 · outbound

This paper cites Language (Technology) is Power: A Critical Survey of "Bias" in NLP.

Bias-Aware Mislabeling Detection via Decoupled Confident Learning Language (Technology) is Power: A Critical Survey of "Bias" in NLP

Reference 11

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Observation 317a1ece-b5dd-4989-a046-00faaf5791fd · outbound

This paper cites Man is to computer programmer as woman is to homemaker? debiasing word embeddings.

Bias-Aware Mislabeling Detection via Decoupled Confident Learning Man is to computer programmer as woman is to homemaker? debiasing word embeddings

Reference 12

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Observation 8007b648-3f9e-456e-8956-cbdc8eeec769 · outbound

This paper cites The challenges of data quality and data quality assessment in the big data era.

Bias-Aware Mislabeling Detection via Decoupled Confident Learning The challenges of data quality and data quality assessment in the big data era

Reference 13

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Observation fd51ec92-4a48-4947-aff7-360edabcaf75 · outbound

This paper cites Adaptive sampling strategies to construct equitable training datasets.

Bias-Aware Mislabeling Detection via Decoupled Confident Learning Adaptive sampling strategies to construct equitable training datasets

Reference 14

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Unavailable: canonical work link unavailable.

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Observation d0a4f7f6-9c56-472c-aadb-5106a14e16a9 · outbound

This paper cites Semantics derived automatically from language corpora contain human-like biases.

Bias-Aware Mislabeling Detection via Decoupled Confident Learning Semantics derived automatically from language corpora contain human-like biases

Reference 15

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Observation 16a89498-9ea8-48aa-9e2d-f05d2c4e2728 · outbound

This paper cites Internet, social media and online hate speech.

Bias-Aware Mislabeling Detection via Decoupled Confident Learning Internet, social media and online hate speech

Reference 16

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Observation ee5c870c-8cff-4f51-b6d5-e0ccb9d74c9d · outbound

This paper cites Understanding and utilizing deep neural networks trained with noisy labels.

Bias-Aware Mislabeling Detection via Decoupled Confident Learning Understanding and utilizing deep neural networks trained with noisy labels

Reference 17

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Source-reported events for the cited work

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Observation 9951a909-3a52-4456-9447-721734547c2d · outbound

This paper cites Modeling spatial and temporal set-based constraints during conceptual database design.

Bias-Aware Mislabeling Detection via Decoupled Confident Learning Modeling spatial and temporal set-based constraints during conceptual database design

Reference 18

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Source-reported events for the cited work

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Observation eaa97c43-6acc-45f6-86d3-477deb3420c1 · outbound

This paper cites Hate speech classifiers learn normative social stereotypes.

Bias-Aware Mislabeling Detection via Decoupled Confident Learning Hate speech classifiers learn normative social stereotypes

Reference 19

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 9c181440-5c39-4652-bc10-31805588fc88 · outbound

This paper cites Dealing with disagree- ments: Looking beyond the majority vote in subjective annotations.

Bias-Aware Mislabeling Detection via Decoupled Confident Learning Dealing with disagree- ments: Looking beyond the majority vote in subjective annotations

Reference 20

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Source-reported events for the cited work

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Observation 5ac07418-9c6d-42cf-b3a1-c65ce2202d53 · outbound

This paper cites Competing on analytics.

Bias-Aware Mislabeling Detection via Decoupled Confident Learning Competing on analytics

Reference 21

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation f502292a-837f-4aa7-8bde-93b5d46cd5f2 · outbound

This paper cites Maximum likelihood estimation of observer error-rates using the em algorithm.

Bias-Aware Mislabeling Detection via Decoupled Confident Learning Maximum likelihood estimation of observer error-rates using the em algorithm

Reference 22

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 1ba88b1c-b8ce-4178-88fe-b8405724e273 · outbound

This paper cites Algorithmic fairness in 30 business analytics: Directions for research and practice.

Bias-Aware Mislabeling Detection via Decoupled Confident Learning Algorithmic fairness in 30 business analytics: Directions for research and practice

Reference 23

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation ddf31d8c-823f-47a4-a8de-3ad6141e2a89 · outbound

This paper cites Reassessing data quality for information products.

Bias-Aware Mislabeling Detection via Decoupled Confident Learning Reassessing data quality for information products

Reference 24

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No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 0ac2efc1-780d-4461-990e-de49a845851a · outbound

This paper cites A checklist to combat cognitive biases in crowdsourcing.

Bias-Aware Mislabeling Detection via Decoupled Confident Learning A checklist to combat cognitive biases in crowdsourcing

Reference 25

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 48ba64f3-9c42-4616-9acd-35dcbfee53e6 · outbound

This paper cites Decoupled classifiers for group-fair and efficient machine learning.

Bias-Aware Mislabeling Detection via Decoupled Confident Learning Decoupled classifiers for group-fair and efficient machine learning

Reference 26

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 35fa5f93-28dd-45df-b619-e5f568c62475 · outbound

This paper cites Cognitive biases in crowdsourcing.

Bias-Aware Mislabeling Detection via Decoupled Confident Learning Cognitive biases in crowdsourcing

Reference 27

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 6f2b628f-362a-49f9-b17a-0baac4c09ffc · outbound

This paper cites The foundations of cost-sensitive learning.

Bias-Aware Mislabeling Detection via Decoupled Confident Learning The foundations of cost-sensitive learning

Reference 28

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 8724b9a8-a6a2-4931-9e2e-13d66f3260ad · outbound

This paper cites Fairness evaluation in presence of biased noisy labels.

Bias-Aware Mislabeling Detection via Decoupled Confident Learning Fairness evaluation in presence of biased noisy labels

Reference 29

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 023da054-9fe0-46ab-ad3c-30206a1a9923 · outbound

This paper cites Classification in the presence of label noise: a survey.

Bias-Aware Mislabeling Detection via Decoupled Confident Learning Classification in the presence of label noise: a survey

Reference 30

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:51:00.251694Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 6e9c46ec-9f42-4301-aade-2f8fe8a0f67b · outbound

This paper cites “un” fair machine learning algorithms.

Bias-Aware Mislabeling Detection via Decoupled Confident Learning “un” fair machine learning algorithms

Reference 31

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verified fuzzy
raw_fallback, observed 2026-08-06T18:51:00.242728Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 4ff324a7-0efe-4ad4-8e5f-d8df4bb80fd3 · outbound

This paper cites Artificial intelligence and algorithmic bias: Source, detection, mitigation, and implications.

Bias-Aware Mislabeling Detection via Decoupled Confident Learning Artificial intelligence and algorithmic bias: Source, detection, mitigation, and implications

Reference 32

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:51:00.234526Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 14e726ce-e8e7-4895-a5d1-b7ccffa99669 · outbound

This paper cites Do electronic health record systems increase medicare reimbursements? the moderating effect of the recovery audit program.

Bias-Aware Mislabeling Detection via Decoupled Confident Learning Do electronic health record systems increase medicare reimbursements? the moderating effect of the recovery audit program

Reference 33

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verified fuzzy
raw_fallback, observed 2026-08-06T18:51:00.226226Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 6846abeb-71ec-45c3-9262-e9b43f3402d3 · outbound

This paper cites Training deep neural-networks using a noise adap- tation layer.

Bias-Aware Mislabeling Detection via Decoupled Confident Learning Training deep neural-networks using a noise adap- tation layer

Reference 34

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T18:50:59.571880Z digest=sha256:732833948fd2594569a3db5e0a83e318680d95bdee86b057f609eedea017e33d

Observation da95b13a-6e62-49fd-82cc-946c768fcf9e · outbound

This paper cites Same same, but different: Conditional multi-task learning for demographic-specific toxicity detection.

Bias-Aware Mislabeling Detection via Decoupled Confident Learning Same same, but different: Conditional multi-task learning for demographic-specific toxicity detection

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:51:00.209067Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T18:50:59.574073Z digest=sha256:d738d71cd089a18937409aa9bce07b9ca155e9b8340e851d338db9dd514fdb85

Observation d6685a5d-6e6f-41f7-b137-ce5473358022 · outbound

This paper cites Co-teaching: Robust training of deep neural networks with extremely noisy labels.

Bias-Aware Mislabeling Detection via Decoupled Confident Learning Co-teaching: Robust training of deep neural networks with extremely noisy labels

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:51:00.200260Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T18:50:59.576322Z digest=sha256:83680eb33d4d61002f906b4ee5157df920d65505b517e37b29e18e46537d152f

Observation 40b0a1f4-9786-4eb2-8a37-ba73fcddf22d · outbound

This paper cites Data quality for data science, predictive analytics, and big data in supply chain management: An introduction to the problem and suggestions for research and applications.Int.

Bias-Aware Mislabeling Detection via Decoupled Confident Learning Data quality for data science, predictive analytics, and big data in supply chain management: An introduction to the problem and suggestions for research and applications.Int

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:51:00.192038Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T18:50:59.579186Z digest=sha256:e759f2b613c49cdad0fbd1d78f04ce540f534d784cab3c88aa727078c0d6c91b

Observation b3b4c1a9-36c8-482a-a998-34a8d28d3894 · outbound

This paper cites Racial bias in pain assessment and treatment recommendations, and false beliefs about biological differences between blacks and whites.

Bias-Aware Mislabeling Detection via Decoupled Confident Learning Racial bias in pain assessment and treatment recommendations, and false beliefs about biological differences between blacks and whites

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:51:00.183130Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T18:50:59.581395Z digest=sha256:3e3826dcaf46f6da7247c5f32a39761ab1b4aadb1abfa0cd3d35abb8bf6a1a48

Observation d00e85bd-0d1b-48cf-b239-dcb058d2f1b0 · outbound

This paper cites Crowdsourcing: How the Power of the Crowd is Driving the Future of Business.

Bias-Aware Mislabeling Detection via Decoupled Confident Learning Crowdsourcing: How the Power of the Crowd is Driving the Future of Business

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:51:00.174864Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T18:50:59.583886Z digest=sha256:a07556d88d6adeb55c03a5f5528923654cdbe223b6c33f5b9f71a95a32fc4aa6

Observation e21885df-8c7a-454c-8214-ee0ee2c6ef4f · outbound

This paper cites Differential validity of employment tests by race: A comprehensive review and analysis.

Bias-Aware Mislabeling Detection via Decoupled Confident Learning Differential validity of employment tests by race: A comprehensive review and analysis

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:51:00.166466Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T18:50:59.585930Z digest=sha256:6752392c78599da939d3c97046b2e393542f6db35471d1049b03a07ce4729eaf

Observation 16208b5b-b735-4576-b89b-a974340d6363 · outbound

This paper cites Measurement and fairness.

Bias-Aware Mislabeling Detection via Decoupled Confident Learning Measurement and fairness

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:51:00.158578Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T18:50:59.588128Z digest=sha256:38cf6021e1d2b0e3989197b67cce406c980bebd349a2e0e5284ce06733da181c

Observation 8c559a26-576a-42e7-b5da-2ce81b91f8eb · outbound

This paper cites Emergence of data analytics in the information systems curriculum.

Bias-Aware Mislabeling Detection via Decoupled Confident Learning Emergence of data analytics in the information systems curriculum

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:51:00.148565Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T18:50:59.590462Z digest=sha256:ad1f0b72ec05997726e40a016069420326f0fbe6e5f2276d11b906ca58893059

Observation 6499b1b3-4a77-4993-9589-52f9581d0022 · outbound

This paper cites A systematic review of hate speech automatic detection using natural language processing.

Bias-Aware Mislabeling Detection via Decoupled Confident Learning A systematic review of hate speech automatic detection using natural language processing

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:51:00.140615Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T18:50:59.593143Z digest=sha256:8754f234fc7694fadf159246cfaf44969d1820738f1be54d0712eac66d058147

Observation 34726367-c24b-4650-960b-c954fe66c63d · outbound

This paper cites Identifying and correcting label bias in machine learning.

Bias-Aware Mislabeling Detection via Decoupled Confident Learning Identifying and correcting label bias in machine learning

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:51:00.132975Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T18:50:59.595507Z digest=sha256:1683a500a74c7deddb1b1434a19914ffd056241161aabf5e7cccc12d94ba4398

Observation a5200dc6-6ad5-4f4e-b697-b4628913702a · outbound

This paper cites Beyond synthetic noise: Deep learning on controlled noisy labels.

Bias-Aware Mislabeling Detection via Decoupled Confident Learning Beyond synthetic noise: Deep learning on controlled noisy labels

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:51:00.125430Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T18:50:59.597655Z digest=sha256:70287eababea0fc1557aa42ada10b2c110ea41137317a03cfb6c3628227f3d49

Observation 1d0f8803-bf8f-401e-ba91-a1a62d949aa5 · outbound

This paper cites Classifying without discriminating.

Bias-Aware Mislabeling Detection via Decoupled Confident Learning Classifying without discriminating

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:51:00.117555Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T18:50:59.599929Z digest=sha256:6fff3688df3f4e288c8680c92ffae701be7e95aa197785ca49afcf524fa41ea0

Observation cf7a10cd-736c-486e-acb3-2533bf5046ed · outbound

This paper cites Measuring a hate speech spectrum with faceted Rasch item response theory and perspective-aware, explainable-by-design deep learning.

Bias-Aware Mislabeling Detection via Decoupled Confident Learning Measuring a hate speech spectrum with faceted Rasch item response theory and perspective-aware, explainable-by-design deep learning

Reference 47

Resolution
unresolved
no resolver link, observed 2026-08-06T18:50:59.601987Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T18:50:59.601987Z digest=sha256:86a5bfbf6d5ed4f18a8056c20310c0c3f5460ffb52a179812a48487800ec862f

Observation 6b09f885-8cc8-4eb6-b4a7-da91d62a510e · outbound

This paper cites Demand-aware career path recommendations: A reinforcement learning approach.

Bias-Aware Mislabeling Detection via Decoupled Confident Learning Demand-aware career path recommendations: A reinforcement learning approach

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:51:00.110047Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T18:50:59.604962Z digest=sha256:372090e43ab7c112ea643a8a38deeffbc766927aba45a3e1f28a31f4e9fd7037

Observation 25641880-e348-4c0a-947c-9ca2a78f16d0 · outbound

This paper cites On data reliability assessment in accounting information systems.

Bias-Aware Mislabeling Detection via Decoupled Confident Learning On data reliability assessment in accounting information systems

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:51:00.102588Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T18:50:59.607627Z digest=sha256:c38fa03bd79067b94392132204b42c76bea3978fea14b70fdb62799f3f6900c8

Observation c8bdee4a-2435-4f19-a11d-800c9becffa3 · outbound

This paper cites When more data lead us astray: Active data acquisition in the presence of label bias.

Bias-Aware Mislabeling Detection via Decoupled Confident Learning When more data lead us astray: Active data acquisition in the presence of label bias

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:51:00.095319Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T18:50:59.610311Z digest=sha256:32bbabd02d05541f741ea42202c7e7710cfa1e9752159e8ef20a05d75e7ec7b4

Observation 7d1d5e47-4ba3-4b38-bb8f-06383969d019 · outbound

This paper cites Label bias: A pervasive and invisibilized problem.

Bias-Aware Mislabeling Detection via Decoupled Confident Learning Label bias: A pervasive and invisibilized problem

Reference 51

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:51:00.088196Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T18:50:59.612494Z digest=sha256:c8c8b307a860bb4ee9f1c98443528b19ddbb9e356a9d1e306621084e65d6ce3b

Observation d7019313-1d08-495f-b7c3-2cc3571e3179 · outbound

This paper cites Detecting and correcting for label shift with black box predictors.

Bias-Aware Mislabeling Detection via Decoupled Confident Learning Detecting and correcting for label shift with black box predictors

Reference 52

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:51:00.081216Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T18:50:59.614917Z digest=sha256:6ee947f00c06e3bd1b2d5e4d8a099ff72a9dbf62ebfa457bdd2c4f4eb3a54486

Observation 2708663a-db96-46fb-b683-93201880ee42 · outbound

This paper cites Financial statement audits and data breaches.

Bias-Aware Mislabeling Detection via Decoupled Confident Learning Financial statement audits and data breaches

Reference 53

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:51:00.074244Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T18:50:59.617117Z digest=sha256:3c0d6b4636c01ac5663d5323525a1bde84e1b01ff4cf19abccb0046f4e445ec0

Observation 6b3efa04-579a-4626-af3d-206a0fa42030 · outbound

This paper cites Data analytics research-informed teaching in a digital technologies curriculum.

Bias-Aware Mislabeling Detection via Decoupled Confident Learning Data analytics research-informed teaching in a digital technologies curriculum

Reference 54

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:51:00.067183Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T18:50:59.619658Z digest=sha256:d647131b0c245c47c7d302bf21f46e564c764d0a59fd4bfbe2e506de10ffe1cd

Observation d74020f5-0f43-405b-b187-653f0ec77103 · outbound

This paper cites Normalized loss functions for deep learning with noisy labels.

Bias-Aware Mislabeling Detection via Decoupled Confident Learning Normalized loss functions for deep learning with noisy labels

Reference 55

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:51:00.059788Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T18:50:59.621822Z digest=sha256:034a47bafb3971c4efc9857675675523a632bef110dda5bc39e43338cc7e0ca6

Observation 4e05f7ba-9290-4936-a8a7-7a3fce249a65 · outbound

This paper cites Using customer analytics to boost corporate performance, 2014.

Bias-Aware Mislabeling Detection via Decoupled Confident Learning Using customer analytics to boost corporate performance, 2014

Reference 56

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:51:00.052623Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T18:50:59.624396Z digest=sha256:e120fc60400bc8bfdc543ad2eb31e3bb92ab74cecc835a766cc9846b67adbd6d

Observation f4a07d8e-cd1a-46a7-a8ee-5d0cd9635dd9 · outbound

This paper cites Community standards – hateful conduct.

Bias-Aware Mislabeling Detection via Decoupled Confident Learning Community standards – hateful conduct

Reference 57

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:51:00.045196Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T18:50:59.626699Z digest=sha256:04331ed9d0f51605fed5adeec021dfa7a2eb892f75baedeb64b2b5318410f0d9

Observation 8dc50f03-17f5-46b0-b6ed-7a6100022f3c · outbound

This paper cites Targets of online hate speech in context: a comparative digital social science analysis of comments on public facebook pages from romania and hungary.

Bias-Aware Mislabeling Detection via Decoupled Confident Learning Targets of online hate speech in context: a comparative digital social science analysis of comments on public facebook pages from romania and hungary

Reference 58

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:51:00.037541Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T18:50:59.629034Z digest=sha256:8e6ef7a55e301788e98f2c930834956957c1005c3db527e632566e14570b594c

Observation 349a1f2a-a7cf-4b5f-a59b-910250ccb5f3 · outbound

This paper cites Prediction-Based Decisions and Fairness: A Catalogue of Choices, Assumptions, and Definitions.

Bias-Aware Mislabeling Detection via Decoupled Confident Learning Prediction-Based Decisions and Fairness: A Catalogue of Choices, Assumptions, and Definitions

Reference 59

Resolution
unresolved
no resolver link, observed 2026-08-06T18:50:59.631555Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T18:50:59.631555Z digest=sha256:99cb8283a2bb9cf066405d34c03671f3a039a6f7a3e2fd17fa0ecac374dfdcd1

Observation 90cb9b6e-79fe-486f-b13d-a7f6d518cfb8 · outbound

This paper cites On the inequity of predicting a while hoping for b.

Bias-Aware Mislabeling Detection via Decoupled Confident Learning On the inequity of predicting a while hoping for b

Reference 60

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:51:00.029704Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T18:50:59.635046Z digest=sha256:62244edc49b54cb5ee98498059c534dc7359cea6f8649f665d2e1913985c0601

Observation 3d5a3b8c-5ee6-46ab-8f1d-a1ceec362961 · outbound

This paper cites Learning with noisy labels.

Bias-Aware Mislabeling Detection via Decoupled Confident Learning Learning with noisy labels

Reference 61

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:51:00.022668Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T18:50:59.637109Z digest=sha256:35c2665de354f39939f9ab529c7a75b1a694fdf1af4b5944fcb0615a0823d5a7

Observation 65afe578-1928-4d8a-8cc4-96aa4f7efb65 · outbound

This paper cites Ai risk management framework (ai rmf) playbook, 2023.

Bias-Aware Mislabeling Detection via Decoupled Confident Learning Ai risk management framework (ai rmf) playbook, 2023

Reference 62

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:51:00.015285Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T18:50:59.639419Z digest=sha256:f389e456763dcb8ec318bbda1ec6aec0e282907ac7da0fc510aea7cc932bf890

Observation a6eb1938-4ed1-4efa-a954-1e6e7bf7e722 · outbound

This paper cites Confident learning: Estimating uncertainty in dataset labels.

Bias-Aware Mislabeling Detection via Decoupled Confident Learning Confident learning: Estimating uncertainty in dataset labels

Reference 63

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:51:00.007582Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T18:50:59.641827Z digest=sha256:23817101fb3998a205083e50e2dc5cd9df8431736931f67a8a0b07b6f2ed6e54

Observation 0c3ebf63-8da0-4945-b86e-febc1a63766f · outbound

This paper cites Dissecting racial bias in an algorithm used to manage the health of populations.

Bias-Aware Mislabeling Detection via Decoupled Confident Learning Dissecting racial bias in an algorithm used to manage the health of populations

Reference 64

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:51:00.000389Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T18:50:59.644115Z digest=sha256:51b944e382ccb34c331c8629cc6bc0558481d6402b5ceee8d101cb62f5167460

Observation f27b0663-ba64-4a90-8403-714e32fda61a · outbound

This paper cites Crowdsourcing stereotypes: Linguistic bias in metadata generated via gwap.

Bias-Aware Mislabeling Detection via Decoupled Confident Learning Crowdsourcing stereotypes: Linguistic bias in metadata generated via gwap

Reference 65

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:50:59.993189Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T18:50:59.646270Z digest=sha256:fa67cfe5da89eade2041e50185682e50b816d76a5959e7d00117d1b69324269e

Observation 68cca6fd-e900-434a-bc21-e12bedc68e29 · outbound

This paper cites Assessing data quality for information products: impact of selection, projection, and cartesian product.

Bias-Aware Mislabeling Detection via Decoupled Confident Learning Assessing data quality for information products: impact of selection, projection, and cartesian product

Reference 66

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:50:59.985824Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T18:50:59.648742Z digest=sha256:a8c9100a36d38928bfd15fd0de939135ad03167e655514277e9198ff7a0ca8ea

Observation 7a30e1b0-def0-445b-82b5-eec6b2669e8b · outbound

This paper cites Problem formulation and fairness.

Bias-Aware Mislabeling Detection via Decoupled Confident Learning Problem formulation and fairness

Reference 67

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:50:59.978831Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T18:50:59.650915Z digest=sha256:2e34d658d35dd3caf9e09819a129da054f18f6e20f800753550478422a362ccc

Observation 5d7fba4d-6511-4ebe-9070-7584e768e0c9 · outbound

This paper cites Making deep neural networks robust to label noise: A loss correction approach.

Bias-Aware Mislabeling Detection via Decoupled Confident Learning Making deep neural networks robust to label noise: A loss correction approach

Reference 68

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:50:59.971560Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T18:50:59.653240Z digest=sha256:a32cdf8b1f4d91ddaa7f9f780f25d5df4652cf7ad124f177a660b2c7313f5d07

Observation 33269e6b-737e-479a-8db7-babffdfa2165 · outbound

This paper cites Machine bias, 2016.

Bias-Aware Mislabeling Detection via Decoupled Confident Learning Machine bias, 2016

Reference 69

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:50:59.964057Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T18:50:59.655385Z digest=sha256:26615e5a1135775d77c7c379eb81541a4c563d0667ffe2763de55deba9e4b051

Observation f195975e-3eb3-4626-a755-5b366ca927bd · outbound

This paper cites The risk of racial bias in hate speech detection.

Bias-Aware Mislabeling Detection via Decoupled Confident Learning The risk of racial bias in hate speech detection

Reference 70

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:50:59.957194Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T18:50:59.657601Z digest=sha256:f79f77969feaff619846a7ed7c7fd15001adbc4e079f954f73f341c356f3f1df

Observation ec286500-f1ec-47ee-9f54-82986ad66723 · outbound

This paper cites To explain or to predict? Stat.

Bias-Aware Mislabeling Detection via Decoupled Confident Learning To explain or to predict? Stat

Reference 71

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:50:59.950016Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T18:50:59.660042Z digest=sha256:74a14f85c10af315a39f00e5840e3c91572978cf5beafc6c229ffb7abb57184a

Observation 0e434951-4d5f-4153-a3bd-9d4c1ffdb0a2 · outbound

This paper cites Meta- weight-net: Learning an explicit mapping for sample weighting.

Bias-Aware Mislabeling Detection via Decoupled Confident Learning Meta- weight-net: Learning an explicit mapping for sample weighting

Reference 72

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:50:59.943033Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T18:50:59.662412Z digest=sha256:61ff5a946268057548edf1454ce39d275548e4d1d1f1cc1708fbbd1b5f3b6dbc

Observation 54977c40-56c1-418c-8dab-1fb72a3595ef · outbound

This paper cites The interpretation of interaction in contingency tables.

Bias-Aware Mislabeling Detection via Decoupled Confident Learning The interpretation of interaction in contingency tables

Reference 73

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:50:59.935888Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T18:50:59.664935Z digest=sha256:e40fd22d6ea663518aa61348081663c1c8774405ffd7749e90d4155e86720c8c

Observation 600108d3-331f-402b-b746-7106ce27c3a3 · outbound

This paper cites Racial bias in pulse oximetry measurement.

Bias-Aware Mislabeling Detection via Decoupled Confident Learning Racial bias in pulse oximetry measurement

Reference 74

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:50:59.928716Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T18:50:59.667481Z digest=sha256:2a114ba7eac0fc92886f24a0731eea9a3540fb4e59a7f7c81a77e22b6c17c913

Observation e5d70a58-7417-4f40-8e82-5fe1f19f7359 · outbound

This paper cites Inferring 34 ground truth from subjective labelling of venus images.

Bias-Aware Mislabeling Detection via Decoupled Confident Learning Inferring 34 ground truth from subjective labelling of venus images

Reference 75

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:50:59.921407Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T18:50:59.669700Z digest=sha256:8da12e823ddadac98107a8a2be37142d2cabc420622e73cb65aec7759ada781c

Observation fa6b2376-0367-4d92-8dbd-83c5dfaeaa46 · outbound

This paper cites Cheap and fast–but is it good? evaluating non-expert annotations for natural language tasks.

Bias-Aware Mislabeling Detection via Decoupled Confident Learning Cheap and fast–but is it good? evaluating non-expert annotations for natural language tasks

Reference 76

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:50:59.912503Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T18:50:59.672212Z digest=sha256:a597736a086e5927c6871a8d9b82c69e51b9dd762d30ce6e5294d1baea55a9b1

Observation a7750801-1557-4b73-bb67-66784ef11684 · outbound

This paper cites Riedl, and Matthew Lease.

Bias-Aware Mislabeling Detection via Decoupled Confident Learning Riedl, and Matthew Lease

Reference 77

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:50:59.905316Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T18:50:59.674747Z digest=sha256:4fb64708fbdba5b5365116000cfebd193b91d03e69ed0720cdc997665a8226e7

Observation b0281730-200e-4670-a5c9-55203616c815 · outbound

This paper cites Training Convolutional Networks with Noisy Labels.

Bias-Aware Mislabeling Detection via Decoupled Confident Learning Training Convolutional Networks with Noisy Labels

Reference 78

Resolution
unresolved
no resolver link, observed 2026-08-06T18:50:59.676908Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T18:50:59.676908Z digest=sha256:c814340e86ea6139ecbdfbbe683ed27e68dd4fcc589b77feee1244a5ee86d8dc

Observation b39177e9-0fee-4a7e-92fd-5a60c7a9a528 · outbound

This paper cites A framework for understanding sources of harm throughout the machine learning life cycle.

Bias-Aware Mislabeling Detection via Decoupled Confident Learning A framework for understanding sources of harm throughout the machine learning life cycle

Reference 79

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:50:59.898055Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T18:50:59.679520Z digest=sha256:bf92d8efd473cd384f4d28c204a89a024200b04abc97736fe1b76e3769e9f3ba

Observation e47df17b-0567-4cf4-890c-11243afc8ee0 · outbound

This paper cites Improving medical machine learning models with generative balancing for equity and excellence.

Bias-Aware Mislabeling Detection via Decoupled Confident Learning Improving medical machine learning models with generative balancing for equity and excellence

Reference 80

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:50:59.890685Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T18:50:59.681645Z digest=sha256:00fd12d7d54670f6e25ec1b4f32dccf2f5676d46044e631eebb88fe82ee9c507

Observation 8e476d03-f94e-40f6-85ee-64823176c342 · outbound

This paper cites A theory of the learnable.

Bias-Aware Mislabeling Detection via Decoupled Confident Learning A theory of the learnable

Reference 81

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:50:59.882495Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T18:50:59.683760Z digest=sha256:978803360f1090f1e9c3ae961300a2047b4b9514f20496eed55c6e7c444ae702

Observation f229bff9-a626-41ef-991e-7819c93b8e7f · outbound

This paper cites Learning with symmetric label noise: The importance of being unhinged.

Bias-Aware Mislabeling Detection via Decoupled Confident Learning Learning with symmetric label noise: The importance of being unhinged

Reference 82

Resolution
unresolved
no resolver link, observed 2026-08-06T18:50:59.686066Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T18:50:59.686066Z digest=sha256:3d02f8060facc0eb327e76af09ea71764845c56de7bfdcd895f01d6732ea15cc

Observation acf6844d-513f-4977-bad0-f7c892cd03c8 · outbound

This paper cites Challenges and frontiers in abusive content detection.

Bias-Aware Mislabeling Detection via Decoupled Confident Learning Challenges and frontiers in abusive content detection

Reference 83

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:50:59.870662Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T18:50:59.689111Z digest=sha256:fa926f43216b3d4a6352c1e8c4729a5f6f9f0e0f985b026535c83922f068e8aa

Observation d7b63314-eb29-4e71-9a2c-56c7306c55df · outbound

This paper cites Anchoring data quality dimensions in ontological founda- tions.

Bias-Aware Mislabeling Detection via Decoupled Confident Learning Anchoring data quality dimensions in ontological founda- tions

Reference 84

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:50:59.863463Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T18:50:59.692502Z digest=sha256:5e9bf177155ee101f41bcea735f984bd9581fc9c7dd002136ef899d9d81b2c01

Observation 6a69b2e6-c3aa-4910-bdae-c3bf25c8d2db · outbound

This paper cites Fair classification with group-dependent label noise.

Bias-Aware Mislabeling Detection via Decoupled Confident Learning Fair classification with group-dependent label noise

Reference 85

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:50:59.855553Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T18:50:59.694831Z digest=sha256:e1367234f8629fe2e5aa6f8713e8d104a8a47db079a7b18c118b8174c621f8f9

Observation c624c7d3-bead-41c0-a9de-9ad3e837942b · outbound

This paper cites The multidimensional wisdom of crowds.

Bias-Aware Mislabeling Detection via Decoupled Confident Learning The multidimensional wisdom of crowds

Reference 86

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:50:59.847465Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T18:50:59.697937Z digest=sha256:780ea737c134fe2b3b0bdf5671b48376a05636ef29c0b5b1e6337a4fab2a4e8b

Observation c8ceda47-647c-41b1-8931-e71737cb030e · outbound

This paper cites Whose 35 vote should count more: Optimal integration of labels from labelers of unknown expertise.

Bias-Aware Mislabeling Detection via Decoupled Confident Learning Whose 35 vote should count more: Optimal integration of labels from labelers of unknown expertise

Reference 87

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:50:59.839982Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T18:50:59.700356Z digest=sha256:afd48a8570f779ab6b94ac4ced1f5a7aaedbd897a88b7704ab87afd082159b13

Observation 1fa6a0b3-817b-4085-b42d-29dff54f3868 · outbound

This paper cites Modeling annotator expertise: Learning when everybody knows a bit of something.

Bias-Aware Mislabeling Detection via Decoupled Confident Learning Modeling annotator expertise: Learning when everybody knows a bit of something

Reference 88

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:50:59.832479Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T18:50:59.703040Z digest=sha256:6f5857a27445dc878c437fe2520b585b32c04e3ef8a57c9316a315070ad28130

Observation 89ca1d5b-46e2-4ced-a88b-74898da155da · outbound

This paper cites Unlearning bias in language models by partitioning gradients.

Bias-Aware Mislabeling Detection via Decoupled Confident Learning Unlearning bias in language models by partitioning gradients

Reference 89

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:50:59.824604Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T18:50:59.705205Z digest=sha256:8d6e61c4a1d77eff9d911e11a841f48f6c01d1b4779b574302673ac479030309

Observation 73d3fd4f-7c75-423e-987b-5b2708c78145 · outbound

This paper cites Risk scores, label bias, and every- thing but the kitchen sink.

Bias-Aware Mislabeling Detection via Decoupled Confident Learning Risk scores, label bias, and every- thing but the kitchen sink

Reference 90

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:50:59.816144Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T18:50:59.707525Z digest=sha256:5fe71a85141f5d1e9bdf435aec72b8cb328f99a940a0406158b668c8c9f44d20

Observation 6da64f1e-e0db-48a7-b6bc-7f1780f24ef4 · outbound

This paper cites Parametrised data sampling for fairness optimisation.

Bias-Aware Mislabeling Detection via Decoupled Confident Learning Parametrised data sampling for fairness optimisation

Reference 91

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:50:59.808154Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T18:50:59.710139Z digest=sha256:1c563054fa0e7ccf48585a202f9e75b6de3bdfef3382165c5265792f675d8b31

Observation 4827549d-c1e3-47dc-a960-25fbc86ab74c · outbound

This paper cites Learning fair repre- sentations.

Bias-Aware Mislabeling Detection via Decoupled Confident Learning Learning fair repre- sentations

Reference 92

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:50:59.799874Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T18:50:59.713087Z digest=sha256:f1a5bf0e7cfac00858a6abc3e0556b9526bc42fa38a0939bde5565d83593de68

Observation bc32d9a9-7823-4143-b28c-45db294fadf6 · outbound

This paper cites Learning from crowdsourced labeled data: a survey.

Bias-Aware Mislabeling Detection via Decoupled Confident Learning Learning from crowdsourced labeled data: a survey

Reference 93

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:50:59.791871Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T18:50:59.715634Z digest=sha256:a6e3e011ec267cd9456c9e3488dd287e762f31f4bd0f13cb167bcd3a5dc06ed6

Observation 65fb2936-1f49-448b-a18d-1236175bf7e3 · outbound

This paper cites Learning Gender-Neutral Word Embeddings.

Bias-Aware Mislabeling Detection via Decoupled Confident Learning Learning Gender-Neutral Word Embeddings

Reference 94

Resolution
unresolved
no resolver link, observed 2026-08-06T18:50:59.717921Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T18:50:59.717921Z digest=sha256:73a8a2603df40a234daaeef7ceb09951a2c6fccd755b90405fd7de6cf5e0f87c

Observation dec4d6ca-f0ce-4e2d-b1af-ac35cba8bb1b · outbound

This paper cites LB ∗ 𝑔𝑘 and UB∗ 𝑔𝑘 denote the value of LB𝑔𝑘 and UB𝑔𝑘 under condition 1.

Bias-Aware Mislabeling Detection via Decoupled Confident Learning LB ∗ 𝑔𝑘 and UB∗ 𝑔𝑘 denote the value of LB𝑔𝑘 and UB𝑔𝑘 under condition 1

Reference 95

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:50:59.783603Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T18:50:59.720869Z digest=sha256:81734fcb43473be231cf27598227ec60f9dd50cec35db146e89719aa609bad1f

Pith citing papers

No inbound Pith citation observations are available.