Paper Citation Record · LEDGER

Deep Self-Learning From Noisy Labels

As of 16 August 2026, this Paper Citation Record lists 41 of 41 outbound references and 1 inbound Pith citation observation for arXiv:1908.02160.

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

pith.paper-citation-record.v1
1908.02160 v2

Coverage vector

measured 41 of 41 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-14T14:56:01.676581Z

measured 42 of 42 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-16T06:30:59.297886+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-06-26T00:27:41.609691Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

41 of 41 outbound references displayed

verified exact0
verified fuzzy24
unresolved17
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

15
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

Observation 0eedffa2-c820-4cc8-8061-3494f21f7d4d · outbound

This paper cites k-means++: The ad- vantages of careful seeding.

Deep Self-Learning From Noisy Labels k-means++: The ad- vantages of careful seeding

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T14:56:02.277473Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 3cf8c11f-c7aa-4afc-abf7-75cdd1a5cb34 · outbound

This paper cites Imagenet: A large-scale hierarchical image database.

Deep Self-Learning From Noisy Labels Imagenet: A large-scale hierarchical image database

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-14T14:56:01.478301Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 57d8f2ef-f7a2-4bd4-96d9-8c62aed45d9f · outbound

This paper cites A semi-supervised two-stage approach to learning from noisy labels.

Deep Self-Learning From Noisy Labels A semi-supervised two-stage approach to learning from noisy labels

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T14:56:02.251708Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 6a035b74-02e7-41f3-bb41-1689bb094034 · outbound

This paper cites Making risk minimization tolerant to label noise.

Deep Self-Learning From Noisy Labels Making risk minimization tolerant to label noise

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T14:56:02.236464Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 14259497-49d5-4526-8ba5-7790298bfd67 · outbound

This paper cites Fast r-cnn.

Deep Self-Learning From Noisy Labels Fast r-cnn

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-14T14:56:01.495600Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d44939b6-d4e3-41e1-992c-8d7f2b7ef316 · outbound

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

Deep Self-Learning From Noisy Labels Training deep neural-networks using a noise adaptation layer

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T14:56:02.211307Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 69116a20-31d4-46e3-a0b1-ddc44ee7cf9a · outbound

This paper cites Cur- riculumnet: Weakly supervised learning from large-scale web images.

Deep Self-Learning From Noisy Labels Cur- riculumnet: Weakly supervised learning from large-scale web images

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T14:56:02.195704Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 33bd07d5-7134-4ec8-80de-945e528777c5 · outbound

This paper cites Deep residual learning for image recognition.

Deep Self-Learning From Noisy Labels Deep residual learning for image recognition

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-14T14:56:01.511756Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation dfc5601a-5b53-4840-9c90-baba9a7da93d · outbound

This paper cites Using trusted data to train deep networks on labels corrupted by severe noise.

Deep Self-Learning From Noisy Labels Using trusted data to train deep networks on labels corrupted by severe noise

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T14:56:02.168984Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation e55df8a0-fd50-4c9f-811c-e227da7b4715 · outbound

This paper cites Qual- ity management on amazon mechanical turk.

Deep Self-Learning From Noisy Labels Qual- ity management on amazon mechanical turk

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T14:56:02.153512Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 92ffab5b-42f7-4af1-ad82-ae759b6b4d94 · outbound

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

Deep Self-Learning From Noisy Labels Mentornet: Learning data-driven curriculum for very deep neural networks on corrupted labels

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T14:56:02.136863Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 14574ea2-5e30-4372-81ed-e8ff1a068d1b · outbound

This paper cites Learning multiple layers of features from tiny images.

Deep Self-Learning From Noisy Labels Learning multiple layers of features from tiny images

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-14T14:56:01.532386Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation dd5db36f-db8d-4253-bd6b-e0243b545666 · outbound

This paper cites Imagenet classiﬁcation with deep convolutional neural net- works.

Deep Self-Learning From Noisy Labels Imagenet classiﬁcation with deep convolutional neural net- works

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-14T14:56:01.537697Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fd59accb-3b77-4f17-8a60-33e54bac0b41 · outbound

This paper cites Pseudo-label: The simple and efﬁcient semi-supervised learning method for deep neural networks.

Deep Self-Learning From Noisy Labels Pseudo-label: The simple and efﬁcient semi-supervised learning method for deep neural networks

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-14T14:56:01.543101Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 51295327-a4ba-4757-90ed-09af3fb730da · outbound

This paper cites Cleannet: Transfer learning for scalable image classi- ﬁer training with label noise.

Deep Self-Learning From Noisy Labels Cleannet: Transfer learning for scalable image classi- ﬁer training with label noise

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T14:56:02.091446Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 2c6f4ef9-5177-4702-b476-bd36c57a363a · outbound

This paper cites Learning to learn from noisy labeled data.

Deep Self-Learning From Noisy Labels Learning to learn from noisy labeled data

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T14:56:02.075373Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 212599b9-c05f-4f1c-a18a-ec7deb17eb68 · outbound

This paper cites Learning from noisy labels with distillation.

Deep Self-Learning From Noisy Labels Learning from noisy labels with distillation

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T14:56:02.059602Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation cc1cbc4f-2e14-496f-852d-08feded42ba2 · outbound

This paper cites Feature pyramid networks for object detection.

Deep Self-Learning From Noisy Labels Feature pyramid networks for object detection

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-14T14:56:01.563467Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e9dd3d2a-7baf-47e6-b5a8-dec95bf746eb · outbound

This paper cites Microsoft coco: Common objects in context.

Deep Self-Learning From Noisy Labels Microsoft coco: Common objects in context

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-14T14:56:01.568241Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d9a7dbec-991b-4d2f-83ad-41f844cdaa57 · outbound

This paper cites Show, tell and discriminate: Image captioning by self-retrieval with partially labeled data.

Deep Self-Learning From Noisy Labels Show, tell and discriminate: Image captioning by self-retrieval with partially labeled data

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T14:56:02.023484Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 708dbfcd-188b-452b-9c4a-c3e9e67e3021 · outbound

This paper cites Improving referring expression grounding with cross-modal attention-guided erasing.

Deep Self-Learning From Noisy Labels Improving referring expression grounding with cross-modal attention-guided erasing

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T14:56:02.007378Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation d0c9f1d7-36b2-48f0-ab5e-92cdde8487fe · outbound

This paper cites Fully convolutional networks for semantic segmentation.

Deep Self-Learning From Noisy Labels Fully convolutional networks for semantic segmentation

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-14T14:56:01.583020Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 46d3174c-e96b-43df-9cb5-91350ba756ed · outbound

This paper cites A study of the effect of different types of noise on the preci- sion of supervised learning techniques.Artiﬁcial intelligence review, 33(4):275–306, 2010.

Deep Self-Learning From Noisy Labels A study of the effect of different types of noise on the preci- sion of supervised learning techniques.Artiﬁcial intelligence review, 33(4):275–306, 2010

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T14:56:01.981047Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 59587fd0-3c9b-404f-b177-08e8b9c43112 · outbound

This paper cites Learning deconvolution network for semantic segmentation.

Deep Self-Learning From Noisy Labels Learning deconvolution network for semantic segmentation

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-14T14:56:01.592590Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 84f14f3b-3bd0-46b9-aec3-704b72a94eb2 · outbound

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

Deep Self-Learning From Noisy Labels Making deep neural networks robust to label noise: A loss correction approach

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T14:56:01.955103Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation fd24fd11-381f-4490-99b9-210692df6134 · outbound

This paper cites Class noise and supervised learn- ing in medical domains: The effect of feature extraction.

Deep Self-Learning From Noisy Labels Class noise and supervised learn- ing in medical domains: The effect of feature extraction

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T14:56:01.939709Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 36ddc4a7-d5a8-4e50-8e6a-3c052bbdb803 · outbound

This paper cites Yolo9000: better, faster, stronger.

Deep Self-Learning From Noisy Labels Yolo9000: better, faster, stronger

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T14:56:01.923361Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 199fabb6-a34f-40e1-9e33-61e7cacd8a38 · outbound

This paper cites Training Deep Neural Networks on Noisy Labels with Bootstrapping.

Deep Self-Learning From Noisy Labels Training Deep Neural Networks on Noisy Labels with Bootstrapping

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-14T14:56:01.611591Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d03aed3b-faaf-4d72-acc9-2137c3f2e062 · outbound

This paper cites Learning to Reweight Examples for Robust Deep Learning.

Deep Self-Learning From Noisy Labels Learning to Reweight Examples for Robust Deep Learning

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-14T14:56:01.616910Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 08bfe19f-18aa-47e5-8138-fe63da04f28b · outbound

This paper cites Faster r-cnn: Towards real-time object detection with region proposal networks.

Deep Self-Learning From Noisy Labels Faster r-cnn: Towards real-time object detection with region proposal networks

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-14T14:56:01.621721Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 21961585-80e2-44f1-b5d5-e0de33949ed4 · outbound

This paper cites Clustering by fast search and ﬁnd of density peaks.

Deep Self-Learning From Noisy Labels Clustering by fast search and ﬁnd of density peaks

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T14:56:01.897084Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 1cd3b880-729c-4dd0-8e8c-bfc012d745c8 · outbound

This paper cites Training Convolutional Networks with Noisy Labels.

Deep Self-Learning From Noisy Labels Training Convolutional Networks with Noisy Labels

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-14T14:56:01.631883Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4fe9003e-6e41-4441-9b68-0d08143b14ff · outbound

This paper cites Going deeper with convolutions.

Deep Self-Learning From Noisy Labels Going deeper with convolutions

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-14T14:56:01.637135Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1b250018-37ad-401d-a414-94bbe12086d4 · outbound

This paper cites Deepface: Closing the gap to human-level perfor- mance in face veriﬁcation.

Deep Self-Learning From Noisy Labels Deepface: Closing the gap to human-level perfor- mance in face veriﬁcation

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-14T14:56:01.641868Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 14f5dbcf-d1b3-496a-8e77-82c832545ea7 · outbound

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

Deep Self-Learning From Noisy Labels Joint optimization framework for learning with noisy labels

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T14:56:01.859446Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 02c23738-c593-40e9-baf4-bff6d6f20a03 · outbound

This paper cites Toward robustness against label noise in train- ing deep discriminative neural networks.

Deep Self-Learning From Noisy Labels Toward robustness against label noise in train- ing deep discriminative neural networks

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T14:56:01.843068Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation a7f67ce8-c809-4d1f-b133-b32487997847 · outbound

This paper cites Learning from noisy large- scale datasets with minimal supervision.

Deep Self-Learning From Noisy Labels Learning from noisy large- scale datasets with minimal supervision

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T14:56:01.826232Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 2bff8ac9-1a2d-443a-8f67-52d4c95c4c28 · outbound

This paper cites Learning from massive noisy labeled data for im- age classiﬁcation.

Deep Self-Learning From Noisy Labels Learning from massive noisy labeled data for im- age classiﬁcation

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T14:56:01.809322Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 47bf4fc9-3c4a-4497-85cf-06c6fd47ed8a · outbound

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

Deep Self-Learning From Noisy Labels Generalized cross entropy loss for training deep neural networks with noisy labels

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T14:56:01.793364Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation d5ecaec4-1f31-4fa7-a103-d89f99421385 · outbound

This paper cites Pyramid scene parsing network.

Deep Self-Learning From Noisy Labels Pyramid scene parsing network

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-14T14:56:01.671640Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b603b8cc-8390-49ce-85ed-e1e3d75bc93d · outbound

This paper cites Talking face generation by adversarially disentan- gled audio-visual representation.

Deep Self-Learning From Noisy Labels Talking face generation by adversarially disentan- gled audio-visual representation

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T14:56:01.766969Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Pith citing papers

Observation da11483c-90ce-497c-a249-e7d6d2441f70 · inbound

Retrieval-Augmented Personalization with Foundation Models for Wearable Stress Detection cites this paper.

Retrieval-Augmented Personalization with Foundation Models for Wearable Stress Detection Deep Self-Learning From Noisy Labels

Reference 38

Resolution: verified exact; arxiv_id, observed 2026-06-26T00:28:42.735693Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.