Paper Citation Record · LEDGER

NoiseCutMix: A Novel Data Augmentation Approach by Mixing Estimated Noise in Diffusion Models

As of 17 August 2026, this Paper Citation Record lists 24 of 24 outbound references and 0 inbound Pith citation observations for arXiv:2509.00378.

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

pith.paper-citation-record.v1
2509.00378 v1

Coverage vector

measured 24 of 24 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-05T13:44:05.665777Z

measured 24 of 24 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+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

24 of 24 outbound references displayed

verified exact1
verified fuzzy18
unresolved5
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation ea7d818e-076f-40b8-975b-4c5e50a51508 · outbound

This paper cites Advances in diffusion models for image data augmentation: A review of methods, models, evaluation metrics and future research directions.

NoiseCutMix: A Novel Data Augmentation Approach by Mixing Estimated Noise in Diffusion Models Advances in diffusion models for image data augmentation: A review of methods, models, evaluation metrics and future research directions

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T13:44:10.545160Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation bf39ae4f-7f82-4af7-8c8e-368117a5f3ee · outbound

This paper cites an unresolved cited work.

NoiseCutMix: A Novel Data Augmentation Approach by Mixing Estimated Noise in Diffusion Models Unresolved cited work

Reference 2

Resolution: unresolved; raw_fallback, observed 2026-08-05T13:44:10.289410Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation cc0f5663-eb7e-4ffa-bab9-7e51735f29d7 · outbound

This paper cites An image is worth one word: Personalizing text-to-image gen- eration using textual inversion.

NoiseCutMix: A Novel Data Augmentation Approach by Mixing Estimated Noise in Diffusion Models An image is worth one word: Personalizing text-to-image gen- eration using textual inversion

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T13:44:10.071631Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 87efefa9-4e39-4d7d-9663-5a08ab5b2719 · outbound

This paper cites Deep residual learning for image recognition.

NoiseCutMix: A Novel Data Augmentation Approach by Mixing Estimated Noise in Diffusion Models Deep residual learning for image recognition

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T13:44:09.902208Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 1b750dc5-feb5-47e7-8ed4-d14131c757f9 · outbound

This paper cites Classifier-free diffusion guidance.

NoiseCutMix: A Novel Data Augmentation Approach by Mixing Estimated Noise in Diffusion Models Classifier-free diffusion guidance

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T13:44:09.677992Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 39b04404-9499-4c04-9ac3-1d2853f8bc57 · outbound

This paper cites Denoising dif- fusion probabilistic models.

NoiseCutMix: A Novel Data Augmentation Approach by Mixing Estimated Noise in Diffusion Models Denoising dif- fusion probabilistic models

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T13:44:09.434026Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 7e81bb6a-088e-4b60-9657-768c61c32627 · outbound

This paper cites LoRA: Low-Rank Adaptation of Large Language Models.

NoiseCutMix: A Novel Data Augmentation Approach by Mixing Estimated Noise in Diffusion Models LoRA: Low-Rank Adaptation of Large Language Models

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-05T13:44:03.401762Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2c494a1a-422c-4a75-8702-d16728e9837f · outbound

This paper cites Diffusemix: Label- preserving data augmentation with diffusion models.

NoiseCutMix: A Novel Data Augmentation Approach by Mixing Estimated Noise in Diffusion Models Diffusemix: Label- preserving data augmentation with diffusion models

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T13:44:09.166754Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 74d9f377-471f-40d3-b813-8edec15061cc · outbound

This paper cites Genmix: effective data augmentation with generative diffusion model image editing.

NoiseCutMix: A Novel Data Augmentation Approach by Mixing Estimated Noise in Diffusion Models Genmix: effective data augmentation with generative diffusion model image editing

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-05T13:44:03.801579Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b52581f3-eb9d-4d3c-abdd-acaa02362f8d · outbound

This paper cites A comprehensive survey of recent trends in deep learn- ing for digital images augmentation.

NoiseCutMix: A Novel Data Augmentation Approach by Mixing Estimated Noise in Diffusion Models A comprehensive survey of recent trends in deep learn- ing for digital images augmentation

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T13:44:08.916004Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation dfa49df3-3b68-4791-9f2d-847bbc141736 · outbound

This paper cites Adam: A method for stochastic optimization.

NoiseCutMix: A Novel Data Augmentation Approach by Mixing Estimated Noise in Diffusion Models Adam: A method for stochastic optimization

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T13:44:08.727245Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 319c25a2-c7f9-4d20-877b-82e01fad23a5 · outbound

This paper cites Dpm-solver: A fast ode solver for dif- fusion probabilistic model sampling in around 10 steps.

NoiseCutMix: A Novel Data Augmentation Approach by Mixing Estimated Noise in Diffusion Models Dpm-solver: A fast ode solver for dif- fusion probabilistic model sampling in around 10 steps

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T13:44:08.501375Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation c53015b6-b4b1-4f0b-97d2-b69fa9d827e6 · outbound

This paper cites Fine-Grained Visual Classification of Aircraft.

NoiseCutMix: A Novel Data Augmentation Approach by Mixing Estimated Noise in Diffusion Models Fine-Grained Visual Classification of Aircraft

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-05T13:44:04.288446Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3d22edf5-1fd0-4fe0-b2b5-59d52052a12a · outbound

This paper cites Automated flower classification over a large number of classes.

NoiseCutMix: A Novel Data Augmentation Approach by Mixing Estimated Noise in Diffusion Models Automated flower classification over a large number of classes

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T13:44:08.229240Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation f6bce525-d8c3-452a-a05b-d07b47e5692e · outbound

This paper cites High-resolution image syn- thesis with latent diffusion models.

NoiseCutMix: A Novel Data Augmentation Approach by Mixing Estimated Noise in Diffusion Models High-resolution image syn- thesis with latent diffusion models

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T13:44:08.026552Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 8c9d571a-6a3d-466b-9e9b-8c6ad58bc6a4 · outbound

This paper cites A survey on image data augmentation for deep learning.

NoiseCutMix: A Novel Data Augmentation Approach by Mixing Estimated Noise in Diffusion Models A survey on image data augmentation for deep learning

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T13:44:07.860945Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 00de8729-5f8d-412e-8c33-df46a45761fe · outbound

This paper cites Effective data augmentation with diffu- sion models.

NoiseCutMix: A Novel Data Augmentation Approach by Mixing Estimated Noise in Diffusion Models Effective data augmentation with diffu- sion models

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T13:44:07.600930Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 06315654-4c4b-4bd8-9372-f4671d8af89a · outbound

This paper cites The caltech-ucsd birds-200 dataset.

NoiseCutMix: A Novel Data Augmentation Approach by Mixing Estimated Noise in Diffusion Models The caltech-ucsd birds-200 dataset

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T13:44:07.325367Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation bd38219c-f564-46b3-a329-6a8546e3277f · outbound

This paper cites Enhance im- age classification via inter-class image mixup with diffusion model.

NoiseCutMix: A Novel Data Augmentation Approach by Mixing Estimated Noise in Diffusion Models Enhance im- age classification via inter-class image mixup with diffusion model

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T13:44:07.055357Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 841c0e85-ca2a-446f-a36d-0bebb99f3f3e · outbound

This paper cites Image Data Augmentation for Deep Learning: A Survey.

NoiseCutMix: A Novel Data Augmentation Approach by Mixing Estimated Noise in Diffusion Models Image Data Augmentation for Deep Learning: A Survey

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-05T13:44:05.156495Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8a009d80-307b-461a-9f10-b7dd2c3a5854 · outbound

This paper cites Real-fake: Effective training data synthesis through distribution matching.

NoiseCutMix: A Novel Data Augmentation Approach by Mixing Estimated Noise in Diffusion Models Real-fake: Effective training data synthesis through distribution matching

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T13:44:06.912667Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 30427d03-54ee-4c89-aa6d-fd6d61b132dd · outbound

This paper cites Cutmix: Regu- larization strategy to train strong classifiers with localizable features.

NoiseCutMix: A Novel Data Augmentation Approach by Mixing Estimated Noise in Diffusion Models Cutmix: Regu- larization strategy to train strong classifiers with localizable features

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T13:44:06.741762Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 8e1107dd-c153-4bcf-80f5-0a0c4ffac947 · outbound

This paper cites mixup: Beyond empirical risk minimiza- tion.

NoiseCutMix: A Novel Data Augmentation Approach by Mixing Estimated Noise in Diffusion Models mixup: Beyond empirical risk minimiza- tion

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T13:44:06.498644Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 2b8f66be-2975-4537-9a49-eb57e77747b9 · outbound

This paper cites A Survey on Data Augmentation in Large Model Era.

NoiseCutMix: A Novel Data Augmentation Approach by Mixing Estimated Noise in Diffusion Models A Survey on Data Augmentation in Large Model Era

Reference 25

Resolution: verified exact; local_arxiv, observed 2026-08-05T13:44:05.995282Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Pith citing papers

No inbound Pith citation observations are available.