Paper Citation Record · LEDGER

Effective Dual-Region Augmentation for Reduced Reliance on Large Amounts of Labeled Data

As of 23 August 2026, this Paper Citation Record lists 33 of 33 outbound references and 0 inbound Pith citation observations for arXiv:2504.13077.

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

pith.paper-citation-record.v1
2504.13077 v2

Coverage vector

measured 33 of 33 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-16T12:17:15.326918Z

measured 33 of 33 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+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

33 of 33 outbound references displayed

verified exact0
verified fuzzy29
unresolved4
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation f373cad1-79bf-4028-b93c-32e1e4cd104e · outbound

This paper cites D., [Dataset Shift in Machine Learning], The MIT Press (2009).

Effective Dual-Region Augmentation for Reduced Reliance on Large Amounts of Labeled Data D., [Dataset Shift in Machine Learning], The MIT Press (2009)

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:17:15.726220Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation daf2e39b-17d9-44f7-94f2-40da4c4aad61 · outbound

This paper cites Unsupervised domain adaptation by backpropagation,.

Effective Dual-Region Augmentation for Reduced Reliance on Large Amounts of Labeled Data Unsupervised domain adaptation by backpropagation,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:17:15.713253Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation c3071166-944a-48cb-8f8a-95fbfc5061b3 · outbound

This paper cites Adversarial discriminative domain adaptation,.

Effective Dual-Region Augmentation for Reduced Reliance on Large Amounts of Labeled Data Adversarial discriminative domain adaptation,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:17:15.701707Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 9015e7e1-d372-4345-bc8d-880f2afb4eb4 · outbound

This paper cites Conditional adversarial domain adaptation,.

Effective Dual-Region Augmentation for Reduced Reliance on Large Amounts of Labeled Data Conditional adversarial domain adaptation,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:17:15.690350Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 668be72b-07a8-4fcb-93d4-340b77d46c77 · outbound

This paper cites Unsupervised domain adaptation using feature aligned maximum classifier discrepancy,.

Effective Dual-Region Augmentation for Reduced Reliance on Large Amounts of Labeled Data Unsupervised domain adaptation using feature aligned maximum classifier discrepancy,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:17:15.678695Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation b6b4a416-de33-4a07-b80b-bad5ca3f4ff4 · outbound

This paper cites Contrastive test-time adaptation,.

Effective Dual-Region Augmentation for Reduced Reliance on Large Amounts of Labeled Data Contrastive test-time adaptation,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:17:15.664961Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 69014dae-2738-46c9-89b7-33fb62036973 · outbound

This paper cites Generative adversarial nets,.

Effective Dual-Region Augmentation for Reduced Reliance on Large Amounts of Labeled Data Generative adversarial nets,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:17:15.653380Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation d2aba736-c315-4f03-99aa-2b0df9486765 · outbound

This paper cites Training generative adversarial networks with limited data,.

Effective Dual-Region Augmentation for Reduced Reliance on Large Amounts of Labeled Data Training generative adversarial networks with limited data,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:17:15.642159Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 1c0fab85-a0f8-4a6c-b2ca-516af8e0cb8e · outbound

This paper cites Enhancing gans with mmd neural architecture search, pmish activation function, and adaptive rank decomposition,.

Effective Dual-Region Augmentation for Reduced Reliance on Large Amounts of Labeled Data Enhancing gans with mmd neural architecture search, pmish activation function, and adaptive rank decomposition,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:17:15.630540Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 32cf82d4-d5b1-4e2c-8216-71aa20836aa7 · outbound

This paper cites CyCADA: Cycle-consistent adversarial domain adaptation,.

Effective Dual-Region Augmentation for Reduced Reliance on Large Amounts of Labeled Data CyCADA: Cycle-consistent adversarial domain adaptation,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:17:15.618306Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 284f9dc6-7846-4b9d-8770-a88eae5cbbd5 · outbound

This paper cites Liquid warping gan: A unified framework for human motion imitation, appearance transfer and novel view synthesis,.

Effective Dual-Region Augmentation for Reduced Reliance on Large Amounts of Labeled Data Liquid warping gan: A unified framework for human motion imitation, appearance transfer and novel view synthesis,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:17:15.607147Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation a88cbe9a-d4ba-4022-9321-ead0c77ff07d · outbound

This paper cites Enhancing human action recognition with gan-based data augmentation,.

Effective Dual-Region Augmentation for Reduced Reliance on Large Amounts of Labeled Data Enhancing human action recognition with gan-based data augmentation,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:17:15.595449Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation b38f93cc-a181-4397-808b-5180e3080807 · outbound

This paper cites Auggan: Cross domain adaptation with gan-based data augmentation,.

Effective Dual-Region Augmentation for Reduced Reliance on Large Amounts of Labeled Data Auggan: Cross domain adaptation with gan-based data augmentation,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:17:15.583504Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 4ce3a869-18f8-407b-9b02-68964dbcc582 · outbound

This paper cites Learnable data augmentation for one-shot unsupervised domain adaptation,.

Effective Dual-Region Augmentation for Reduced Reliance on Large Amounts of Labeled Data Learnable data augmentation for one-shot unsupervised domain adaptation,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:17:15.570965Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation e43f7b6a-07ff-447b-bdf3-930c37cfabf5 · outbound

This paper cites Adversarial and random transformations for robust domain adaptation and generalization,.

Effective Dual-Region Augmentation for Reduced Reliance on Large Amounts of Labeled Data Adversarial and random transformations for robust domain adaptation and generalization,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:17:15.558591Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation b2f7c0b9-3973-4377-904e-adc27ccec384 · outbound

This paper cites Parameter-efficient person re-identification in the 3d space,.

Effective Dual-Region Augmentation for Reduced Reliance on Large Amounts of Labeled Data Parameter-efficient person re-identification in the 3d space,

Reference 16

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Source-reported events for the cited work

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Observation a05d7a60-c1b8-42b8-8862-c981da20ec18 · outbound

This paper cites Joint discriminative and generative learning for person re-identification,.

Effective Dual-Region Augmentation for Reduced Reliance on Large Amounts of Labeled Data Joint discriminative and generative learning for person re-identification,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:17:15.546751Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 7ccb8840-e6c0-4179-bd99-fabdd3485109 · outbound

This paper cites Unlabeled samples generated by gan improve the person re- identification baseline in vitro,.

Effective Dual-Region Augmentation for Reduced Reliance on Large Amounts of Labeled Data Unlabeled samples generated by gan improve the person re- identification baseline in vitro,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:17:15.534655Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation a1179179-abed-414a-ab2a-5ddab2f73ec1 · outbound

This paper cites An improved cyclegan for data augmentation in person re-identification,.

Effective Dual-Region Augmentation for Reduced Reliance on Large Amounts of Labeled Data An improved cyclegan for data augmentation in person re-identification,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:17:15.521471Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 50105c1c-6240-4809-a68f-1a0b6731d8de · outbound

This paper cites Unpaired image-to-image translation using cycle-consistent adversarial networks,.

Effective Dual-Region Augmentation for Reduced Reliance on Large Amounts of Labeled Data Unpaired image-to-image translation using cycle-consistent adversarial networks,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:17:15.507856Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation da93dbe5-6c7c-4c0a-a678-915032baee5d · outbound

This paper cites Random erasing data augmentation,.

Effective Dual-Region Augmentation for Reduced Reliance on Large Amounts of Labeled Data Random erasing data augmentation,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:17:15.496765Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 48b1bb80-6c0a-4487-980b-eb6938ce98af · outbound

This paper cites A Person Re-identification Data Augmentation Method with Adversarial Defense Effect.

Effective Dual-Region Augmentation for Reduced Reliance on Large Amounts of Labeled Data A Person Re-identification Data Augmentation Method with Adversarial Defense Effect

Reference 22

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Source-reported events for the cited work

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Observation fca75069-3eae-4702-a190-a31748c100ef · outbound

This paper cites U2-net: Going deeper with nested u-structure for salient object detection,.

Effective Dual-Region Augmentation for Reduced Reliance on Large Amounts of Labeled Data U2-net: Going deeper with nested u-structure for salient object detection,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:17:15.484418Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 851befc1-0e04-4f49-ad73-1993f2ea47e4 · outbound

This paper cites Deeper, broader and artier domain generalization,.

Effective Dual-Region Augmentation for Reduced Reliance on Large Amounts of Labeled Data Deeper, broader and artier domain generalization,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:17:15.473481Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 1b88bac5-e8ce-4b41-8836-64c22ad415fc · outbound

This paper cites Cleaning noisy labels by negative ensemble learning for source- free unsupervised domain adaptation,.

Effective Dual-Region Augmentation for Reduced Reliance on Large Amounts of Labeled Data Cleaning noisy labels by negative ensemble learning for source- free unsupervised domain adaptation,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:17:15.462551Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation d28fe15b-0678-41c6-9cb0-da716fba7254 · outbound

This paper cites Deep residual learning for image recognition,.

Effective Dual-Region Augmentation for Reduced Reliance on Large Amounts of Labeled Data Deep residual learning for image recognition,

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-16T12:17:15.301026Z

Source-reported events for the cited work

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Observation 1b919351-1a17-469c-a173-3097b43f34c9 · outbound

This paper cites Scalable person re-identification: A benchmark,.

Effective Dual-Region Augmentation for Reduced Reliance on Large Amounts of Labeled Data Scalable person re-identification: A benchmark,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:17:15.444468Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 52ca7717-8dcc-47f6-87da-cecbf9acc7dd · outbound

This paper cites Performance measures and a data set for multi-target, multi-camera tracking,.

Effective Dual-Region Augmentation for Reduced Reliance on Large Amounts of Labeled Data Performance measures and a data set for multi-target, multi-camera tracking,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:17:15.432403Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 230a6ac4-d839-4500-90a5-6adb0e16513e · outbound

This paper cites Efficientnet: Rethinking model scaling for convolutional neural networks,.

Effective Dual-Region Augmentation for Reduced Reliance on Large Amounts of Labeled Data Efficientnet: Rethinking model scaling for convolutional neural networks,

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:17:15.421499Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 89043f43-e7f5-440a-aa1e-4c4c1c89401e · outbound

This paper cites Domain separation networks,.

Effective Dual-Region Augmentation for Reduced Reliance on Large Amounts of Labeled Data Domain separation networks,

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:17:15.410693Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 7df4a44a-2dc5-4c72-bcac-1ef61b4467f9 · outbound

This paper cites Unsupervised multi-target domain adaptation: An information theoretic approach,.

Effective Dual-Region Augmentation for Reduced Reliance on Large Amounts of Labeled Data Unsupervised multi-target domain adaptation: An information theoretic approach,

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:17:15.399027Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 5e2177c1-2c2a-40b8-98ac-a7e261741efb · outbound

This paper cites Knowledge distillation methods for efficient unsupervised adaptation across multiple domains,.

Effective Dual-Region Augmentation for Reduced Reliance on Large Amounts of Labeled Data Knowledge distillation methods for efficient unsupervised adaptation across multiple domains,

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T12:17:15.387204Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation ea1287b6-cd2e-43fd-bf51-7ff941c4ef44 · outbound

This paper cites Improved Baselines with Momentum Contrastive Learning.

Effective Dual-Region Augmentation for Reduced Reliance on Large Amounts of Labeled Data Improved Baselines with Momentum Contrastive Learning

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-16T12:17:15.326918Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

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