Paper Citation Record · LEDGER

Selfish Evolution: Making Discoveries in Extreme Label Noise with the Help of Overfitting Dynamics

As of 17 August 2026, this Paper Citation Record lists 38 of 38 outbound references and 0 inbound Pith citation observations for arXiv:2412.00077.

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

pith.paper-citation-record.v1
2412.00077 v1

Coverage vector

measured 38 of 38 reference resolution

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measured 38 of 38 standing notices

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Pith citing papers itemized under the disclosed page cap.

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Reference resolution

38 of 38 outbound references displayed

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External citation measurements

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Outbound references

Observation 551f167b-744b-4d84-b231-cfb74d9fc2a9 · outbound

This paper cites The lsst desc dc2 simulated sky survey.

Selfish Evolution: Making Discoveries in Extreme Label Noise with the Help of Overfitting Dynamics The lsst desc dc2 simulated sky survey

Reference 1

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Observation 2e4c7ea8-1514-495e-99ac-15965f51fd39 · outbound

This paper cites DESC DC2 Data Release Note.

Selfish Evolution: Making Discoveries in Extreme Label Noise with the Help of Overfitting Dynamics DESC DC2 Data Release Note

Reference 2

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Observation 71cb7cfc-6525-430c-911e-359173ca53eb · outbound

This paper cites Image classification with deep learning in the presence of noisy labels: A survey.

Selfish Evolution: Making Discoveries in Extreme Label Noise with the Help of Overfitting Dynamics Image classification with deep learning in the presence of noisy labels: A survey

Reference 3

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Observation 586f27da-3686-4ff9-85ee-2d81314ed954 · outbound

This paper cites A closer look at memorization in deep networks.

Selfish Evolution: Making Discoveries in Extreme Label Noise with the Help of Overfitting Dynamics A closer look at memorization in deep networks

Reference 4

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Observation ca141ed6-30b2-490e-8dd2-447b322b4265 · outbound

This paper cites Identifying mis- labeled training data.

Selfish Evolution: Making Discoveries in Extreme Label Noise with the Help of Overfitting Dynamics Identifying mis- labeled training data

Reference 5

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Observation cb033717-3cd1-4793-b290-798446bf7936 · outbound

This paper cites Ai-enhanced citizen science discovery of an ac- tive asteroid:(410590) 2008 gb140.

Selfish Evolution: Making Discoveries in Extreme Label Noise with the Help of Overfitting Dynamics Ai-enhanced citizen science discovery of an ac- tive asteroid:(410590) 2008 gb140

Reference 6

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Observation 1429b24f-54c7-4562-92f5-4486d9eb110e · outbound

This paper cites The active asteroids citizen science program: Overview and first results.

Selfish Evolution: Making Discoveries in Extreme Label Noise with the Help of Overfitting Dynamics The active asteroids citizen science program: Overview and first results

Reference 7

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Observation 8c512121-5935-4bff-9d6b-8e620de723b5 · outbound

This paper cites Understanding Self-Distillation in the Presence of Label Noise.

Selfish Evolution: Making Discoveries in Extreme Label Noise with the Help of Overfitting Dynamics Understanding Self-Distillation in the Presence of Label Noise

Reference 8

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Observation 40b28ada-994e-41bd-996a-c7d718d0332a · outbound

This paper cites Expertise-based Weighting for Regression Models with Noisy Labels.

Selfish Evolution: Making Discoveries in Extreme Label Noise with the Help of Overfitting Dynamics Expertise-based Weighting for Regression Models with Noisy Labels

Reference 9

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Observation 7dd313d5-5e9f-42e3-91fc-75bd324378cf · outbound

This paper cites Classification in the presence of label noise: a survey.IEEE transactions on neural networks and learning systems, 25(5):845– 869, 2013.

Selfish Evolution: Making Discoveries in Extreme Label Noise with the Help of Overfitting Dynamics Classification in the presence of label noise: a survey.IEEE transactions on neural networks and learning systems, 25(5):845– 869, 2013

Reference 10

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Observation 4c9b2e0d-f591-4bc9-b643-689f5f501e79 · outbound

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

Selfish Evolution: Making Discoveries in Extreme Label Noise with the Help of Overfitting Dynamics Classification in the presence of label noise: A survey

Reference 11

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Observation fc1413ed-2c60-4d97-9299-0e190e00f852 · outbound

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

Selfish Evolution: Making Discoveries in Extreme Label Noise with the Help of Overfitting Dynamics Co-teaching: Robust training of deep neu- ral networks with extremely noisy labels

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:56:54.945312Z

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Observation aac98422-4b95-48d0-9b38-34f0fa6dd642 · outbound

This paper cites Learning from Training Dynamics: Identifying Mislabeled Data Beyond Manually Designed Features.

Selfish Evolution: Making Discoveries in Extreme Label Noise with the Help of Overfitting Dynamics Learning from Training Dynamics: Identifying Mislabeled Data Beyond Manually Designed Features

Reference 13

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Observation a4d53c96-e06b-449c-916a-fa88f10967e7 · outbound

This paper cites Mentornet: Learning data-driven cur- riculum for very deep neural networks on corrupted labels.

Selfish Evolution: Making Discoveries in Extreme Label Noise with the Help of Overfitting Dynamics Mentornet: Learning data-driven cur- riculum for very deep neural networks on corrupted labels

Reference 14

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Observation 93579483-d60b-478e-83cf-7265e1dfedda · outbound

This paper cites Improving Generalization Performance by Switching from Adam to SGD.

Selfish Evolution: Making Discoveries in Extreme Label Noise with the Help of Overfitting Dynamics Improving Generalization Performance by Switching from Adam to SGD

Reference 15

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Observation 2b057de5-536b-461d-9621-923823b0f07c · outbound

This paper cites Adam: A Method for Stochastic Optimization.

Selfish Evolution: Making Discoveries in Extreme Label Noise with the Help of Overfitting Dynamics Adam: A Method for Stochastic Optimization

Reference 16

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Observation 0c49f2db-a72c-4ea7-b7ce-157e2abeeac4 · outbound

This paper cites Uncertainty based detection and relabeling of noisy image labels.

Selfish Evolution: Making Discoveries in Extreme Label Noise with the Help of Overfitting Dynamics Uncertainty based detection and relabeling of noisy image labels

Reference 17

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Observation 63efb5eb-6eb8-4428-b116-1b27a846aed3 · outbound

This paper cites Learning mul- tiple layers of features from tiny images.

Selfish Evolution: Making Discoveries in Extreme Label Noise with the Help of Overfitting Dynamics Learning mul- tiple layers of features from tiny images

Reference 18

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Observation 133e0c77-be93-44bc-9f32-d5dc0e3dcc55 · outbound

This paper cites Mnist handwritten digit database, 2010.

Selfish Evolution: Making Discoveries in Extreme Label Noise with the Help of Overfitting Dynamics Mnist handwritten digit database, 2010

Reference 19

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Observation acf47fb4-63c7-44f7-b702-b1b0db221444 · outbound

This paper cites Gradient Descent with Early Stopping is Provably Robust to Label Noise for Overparameterized Neural Networks.

Selfish Evolution: Making Discoveries in Extreme Label Noise with the Help of Overfitting Dynamics Gradient Descent with Early Stopping is Provably Robust to Label Noise for Overparameterized Neural Networks

Reference 20

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Observation ab0ed85e-e2fd-43a1-8129-fea7a360f719 · outbound

This paper cites Early-learning regu- larization prevents memorization of noisy labels.

Selfish Evolution: Making Discoveries in Extreme Label Noise with the Help of Overfitting Dynamics Early-learning regu- larization prevents memorization of noisy labels

Reference 21

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Observation 91b34a89-fa80-4e2d-b815-5175ac60197b · outbound

This paper cites Machine learning for the zwicky transient facility.

Selfish Evolution: Making Discoveries in Extreme Label Noise with the Help of Overfitting Dynamics Machine learning for the zwicky transient facility

Reference 22

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Observation c2b6615f-bbe3-416f-a4b4-e4fd05720fc2 · outbound

This paper cites To- wards theoretically understanding why sgd.

Selfish Evolution: Making Discoveries in Extreme Label Noise with the Help of Overfitting Dynamics To- wards theoretically understanding why sgd

Reference 23

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Observation f75839c9-907e-4bf4-96a1-0df4e7f6055c · outbound

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

Selfish Evolution: Making Discoveries in Extreme Label Noise with the Help of Overfitting Dynamics Making deep neural networks robust to label noise: A loss correction approach

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:56:54.838815Z

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Observation 399d1c7c-2e12-4e47-b92f-d2f4bbfe03d8 · outbound

This paper cites Improving Data Quality with Training Dynamics of Gradient Boosting Decision Trees.

Selfish Evolution: Making Discoveries in Extreme Label Noise with the Help of Overfitting Dynamics Improving Data Quality with Training Dynamics of Gradient Boosting Decision Trees

Reference 25

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Observation 586df344-e5b7-4a08-a505-5e415baca774 · outbound

This paper cites Deep learning approach to real-bogus classification for lsst alert production.

Selfish Evolution: Making Discoveries in Extreme Label Noise with the Help of Overfitting Dynamics Deep learning approach to real-bogus classification for lsst alert production

Reference 26

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Observation 03009239-82da-4a3f-b59d-c371ebd39d3e · outbound

This paper cites Report on the performance of im- age differencing from the perspective of the learning- based classifier task.

Selfish Evolution: Making Discoveries in Extreme Label Noise with the Help of Overfitting Dynamics Report on the performance of im- age differencing from the perspective of the learning- based classifier task

Reference 27

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Observation ac11abe0-dd39-4b77-ad2b-0ffd6067e576 · outbound

This paper cites Real-bogus classifier – status report.

Selfish Evolution: Making Discoveries in Extreme Label Noise with the Help of Overfitting Dynamics Real-bogus classifier – status report

Reference 28

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Observation 1fa7653b-941a-4e8a-85dd-d680857a6e1c · outbound

This paper cites Effective image differencing with convolutional neural networks for real-time transient hunting.

Selfish Evolution: Making Discoveries in Extreme Label Noise with the Help of Overfitting Dynamics Effective image differencing with convolutional neural networks for real-time transient hunting

Reference 29

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This paper cites 2016 uu121: An active asteroid discovery via ai- enhanced citizen science.

Selfish Evolution: Making Discoveries in Extreme Label Noise with the Help of Overfitting Dynamics 2016 uu121: An active asteroid discovery via ai- enhanced citizen science

Reference 30

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Observation fde02e94-26af-4f29-ad44-0914617f9a8e · outbound

This paper cites Choice over effort: Mapping and diagnosing augmented whole slide image datasets with training dynamics.

Selfish Evolution: Making Discoveries in Extreme Label Noise with the Help of Overfitting Dynamics Choice over effort: Mapping and diagnosing augmented whole slide image datasets with training dynamics

Reference 31

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Observation 63f01ebe-07b1-4e55-b8e7-24111c540cf7 · outbound

This paper cites Learning from noisy labels with deep neural networks: A survey.

Selfish Evolution: Making Discoveries in Extreme Label Noise with the Help of Overfitting Dynamics Learning from noisy labels with deep neural networks: A survey

Reference 32

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This paper cites Smith, and Yejin Choi.

Selfish Evolution: Making Discoveries in Extreme Label Noise with the Help of Overfitting Dynamics Smith, and Yejin Choi

Reference 33

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Observation 792ce83c-81e9-46d8-a645-80370a5b5778 · outbound

This paper cites Joint optimization framework for learning with noisy labels.

Selfish Evolution: Making Discoveries in Extreme Label Noise with the Help of Overfitting Dynamics Joint optimization framework for learning with noisy labels

Reference 34

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Observation eb24d644-ce9d-4c7d-aa0c-bff5d8764cef · outbound

This paper cites Learning with Noisy Labels Revisited: A Study Using Real-World Human Annotations.

Selfish Evolution: Making Discoveries in Extreme Label Noise with the Help of Overfitting Dynamics Learning with Noisy Labels Revisited: A Study Using Real-World Human Annotations

Reference 35

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This paper cites How does disagreement help generalization against label corrup- tion? In International Conference on Machine Learn- ing, 2019.

Selfish Evolution: Making Discoveries in Extreme Label Noise with the Help of Overfitting Dynamics How does disagreement help generalization against label corrup- tion? In International Conference on Machine Learn- ing, 2019

Reference 36

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Observation 00d7d10c-614f-4c0e-a720-b5f7efecb744 · outbound

This paper cites Generalized cross entropy loss for training deep neural networks with noisy labels.

Selfish Evolution: Making Discoveries in Extreme Label Noise with the Help of Overfitting Dynamics Generalized cross entropy loss for training deep neural networks with noisy labels

Reference 37

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Observation 71989fb1-6c2c-4bfb-9bd1-0fa344060037 · outbound

This paper cites Un- certainty modeling for robust domain adaptation under noisy environments.

Selfish Evolution: Making Discoveries in Extreme Label Noise with the Help of Overfitting Dynamics Un- certainty modeling for robust domain adaptation under noisy environments

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:56:54.678566Z

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