Paper Citation Record · LEDGER

PoGDiff: Product-of-Gaussians Diffusion Models for Imbalanced Text-to-Image Generation

As of 10 August 2026, this Paper Citation Record lists 59 of 59 outbound references and 1 inbound Pith citation observation for arXiv:2502.08106.

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

pith.paper-citation-record.v1
2502.08106 v3

Coverage vector

measured 59 of 59 reference resolution

Typed states for the displayed outbound observations.

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measured 60 of 60 standing notices

One-hop event checks from named stored sources.

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measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

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measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-07T23:07:20.219779Z

Reference resolution

59 of 59 outbound references displayed

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External citation measurements

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Outbound references

Observation 78ce380c-5e66-46cf-beb0-73d3d394fad6 · outbound

This paper cites Denoising diffusion probabilistic models.

PoGDiff: Product-of-Gaussians Diffusion Models for Imbalanced Text-to-Image Generation Denoising diffusion probabilistic models

Reference 1

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Observation 8b2df18c-84a3-49c3-b71c-cf75e0c6a35f · outbound

This paper cites Score-Based Generative Modeling through Stochastic Differential Equations.

PoGDiff: Product-of-Gaussians Diffusion Models for Imbalanced Text-to-Image Generation Score-Based Generative Modeling through Stochastic Differential Equations

Reference 2

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Observation ba044914-6542-4858-bf3f-a8066899ed72 · outbound

This paper cites Denoising Diffusion Implicit Models.

PoGDiff: Product-of-Gaussians Diffusion Models for Imbalanced Text-to-Image Generation Denoising Diffusion Implicit Models

Reference 3

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Observation efbc7e05-73fb-419f-b071-11f8e3d023c9 · outbound

This paper cites Improved denoising diffusion probabilistic models.

PoGDiff: Product-of-Gaussians Diffusion Models for Imbalanced Text-to-Image Generation Improved denoising diffusion probabilistic models

Reference 4

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Observation d640ca33-6394-4359-85df-1b806818694c · outbound

This paper cites Conditional Stochastic Interpolation for Generative Learning.

PoGDiff: Product-of-Gaussians Diffusion Models for Imbalanced Text-to-Image Generation Conditional Stochastic Interpolation for Generative Learning

Reference 5

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Observation e2b1e770-392a-4478-a2f1-5a3a966e3bf1 · outbound

This paper cites Cascaded diffusion models for high fidelity image generation.

PoGDiff: Product-of-Gaussians Diffusion Models for Imbalanced Text-to-Image Generation Cascaded diffusion models for high fidelity image generation

Reference 6

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Observation 73cab4c2-fa78-4ed3-bce1-cca2ff0b9c93 · outbound

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

PoGDiff: Product-of-Gaussians Diffusion Models for Imbalanced Text-to-Image Generation High- resolution image synthesis with latent diffusion models

Reference 7

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Observation b8f167f7-96bd-425e-b7a2-c80c96d0b302 · outbound

This paper cites Photorealistic text-to-image diffusion models with deep language understanding.

PoGDiff: Product-of-Gaussians Diffusion Models for Imbalanced Text-to-Image Generation Photorealistic text-to-image diffusion models with deep language understanding

Reference 8

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Observation b6305f8e-2274-4a70-bdd7-f93dca879d12 · outbound

This paper cites Classifier-Free Diffusion Guidance.

PoGDiff: Product-of-Gaussians Diffusion Models for Imbalanced Text-to-Image Generation Classifier-Free Diffusion Guidance

Reference 9

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Observation 5405def9-944b-41b2-a179-41bb6749a9c8 · outbound

This paper cites DiffWave: A Versatile Diffusion Model for Audio Synthesis.

PoGDiff: Product-of-Gaussians Diffusion Models for Imbalanced Text-to-Image Generation DiffWave: A Versatile Diffusion Model for Audio Synthesis

Reference 10

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Observation 1bc4935d-04e4-4594-bf15-f50aa173acd8 · outbound

This paper cites Diffusion probabilistic models for 3d point cloud generation.

PoGDiff: Product-of-Gaussians Diffusion Models for Imbalanced Text-to-Image Generation Diffusion probabilistic models for 3d point cloud generation

Reference 11

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Observation 7b7d1e5d-4812-4060-92c9-0644ffe26083 · outbound

This paper cites DreamFusion: Text-to-3D using 2D Diffusion.

PoGDiff: Product-of-Gaussians Diffusion Models for Imbalanced Text-to-Image Generation DreamFusion: Text-to-3D using 2D Diffusion

Reference 12

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Observation ac5c8596-9674-4696-bd5b-fe5127c49cfc · outbound

This paper cites MVDream: Multi-view Diffusion for 3D Generation.

PoGDiff: Product-of-Gaussians Diffusion Models for Imbalanced Text-to-Image Generation MVDream: Multi-view Diffusion for 3D Generation

Reference 13

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Observation 121aaf3b-7352-43e3-b43c-3a89e9875dd4 · outbound

This paper cites Brain imaging generation with latent diffusion models.

PoGDiff: Product-of-Gaussians Diffusion Models for Imbalanced Text-to-Image Generation Brain imaging generation with latent diffusion models

Reference 14

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Observation ed7f17aa-222c-408b-adc6-3008cc5bf770 · outbound

This paper cites Class-balancing diffusion models.

PoGDiff: Product-of-Gaussians Diffusion Models for Imbalanced Text-to-Image Generation Class-balancing diffusion models

Reference 15

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Observation bd3ef601-3b2b-486e-b89f-ff6898fa29d1 · outbound

This paper cites Laion- 5b: An open large-scale dataset for training next generation image-text models.

PoGDiff: Product-of-Gaussians Diffusion Models for Imbalanced Text-to-Image Generation Laion- 5b: An open large-scale dataset for training next generation image-text models

Reference 16

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Observation 183b5d5b-0e8c-47bb-8814-b57492e0c9c3 · outbound

This paper cites Smote: synthetic minority over-sampling technique.

PoGDiff: Product-of-Gaussians Diffusion Models for Imbalanced Text-to-Image Generation Smote: synthetic minority over-sampling technique

Reference 17

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Observation 20aa96fe-fe1e-4de0-93cc-3f1b2dce9973 · outbound

This paper cites Learning from imbalanced data.

PoGDiff: Product-of-Gaussians Diffusion Models for Imbalanced Text-to-Image Generation Learning from imbalanced data

Reference 18

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Observation 8a3b181e-bedd-43f2-9162-8eaecfdc08b5 · outbound

This paper cites Smote for regression.

PoGDiff: Product-of-Gaussians Diffusion Models for Imbalanced Text-to-Image Generation Smote for regression

Reference 19

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This paper cites Smogn: a pre-processing approach for imbalanced regression.

PoGDiff: Product-of-Gaussians Diffusion Models for Imbalanced Text-to-Image Generation Smogn: a pre-processing approach for imbalanced regression

Reference 20

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This paper cites Rebagg: Resampled bagging for imbalanced regression.

PoGDiff: Product-of-Gaussians Diffusion Models for Imbalanced Text-to-Image Generation Rebagg: Resampled bagging for imbalanced regression

Reference 21

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Observation 08334433-b90a-4d91-a7c1-6678b3d204d2 · outbound

This paper cites Delving into deep imbalanced regression.

PoGDiff: Product-of-Gaussians Diffusion Models for Imbalanced Text-to-Image Generation Delving into deep imbalanced regression

Reference 22

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Observation d3b842a6-0261-4111-bd93-1246e60a085c · outbound

This paper cites Balanced mse for imbalanced visual regression.

PoGDiff: Product-of-Gaussians Diffusion Models for Imbalanced Text-to-Image Generation Balanced mse for imbalanced visual regression

Reference 23

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Observation d957c58e-1eb4-4b38-89d1-371f45851039 · outbound

This paper cites RankSim: Ranking Similarity Regularization for Deep Imbalanced Regression.

PoGDiff: Product-of-Gaussians Diffusion Models for Imbalanced Text-to-Image Generation RankSim: Ranking Similarity Regularization for Deep Imbalanced Regression

Reference 24

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This paper cites ConR: Contrastive Regularizer for Deep Imbalanced Regression.

PoGDiff: Product-of-Gaussians Diffusion Models for Imbalanced Text-to-Image Generation ConR: Contrastive Regularizer for Deep Imbalanced Regression

Reference 25

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Observation 8848fcc9-b6f5-4e9e-bd8f-aed1161dd6c0 · outbound

This paper cites Variational imbalanced regression: Fair uncertainty quantification via probabilistic smoothing.

PoGDiff: Product-of-Gaussians Diffusion Models for Imbalanced Text-to-Image Generation Variational imbalanced regression: Fair uncertainty quantification via probabilistic smoothing

Reference 26

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Observation bdba097f-c5c4-449d-944c-7570d12176d0 · outbound

This paper cites Dreambooth: Fine tuning text-to-image diffusion models for subject-driven generation.

PoGDiff: Product-of-Gaussians Diffusion Models for Imbalanced Text-to-Image Generation Dreambooth: Fine tuning text-to-image diffusion models for subject-driven generation

Reference 27

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This paper cites Multi- concept customization of text-to-image diffusion.

PoGDiff: Product-of-Gaussians Diffusion Models for Imbalanced Text-to-Image Generation Multi- concept customization of text-to-image diffusion

Reference 28

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This paper cites Photomaker: Customizing realistic human photos via stacked id embedding.

PoGDiff: Product-of-Gaussians Diffusion Models for Imbalanced Text-to-Image Generation Photomaker: Customizing realistic human photos via stacked id embedding

Reference 29

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Observation 5aaa29ad-7d08-4a77-a7ab-0f47ab2eb048 · outbound

This paper cites Long-tailed diffusion models with oriented calibration.

PoGDiff: Product-of-Gaussians Diffusion Models for Imbalanced Text-to-Image Generation Long-tailed diffusion models with oriented calibration

Reference 30

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This paper cites Label-Noise Robust Diffusion Models.

PoGDiff: Product-of-Gaussians Diffusion Models for Imbalanced Text-to-Image Generation Label-Noise Robust Diffusion Models

Reference 31

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This paper cites Finetuning Text-to-Image Diffusion Models for Fairness.

PoGDiff: Product-of-Gaussians Diffusion Models for Imbalanced Text-to-Image Generation Finetuning Text-to-Image Diffusion Models for Fairness

Reference 32

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This paper cites Training unbiased diffusion models from biased dataset.

PoGDiff: Product-of-Gaussians Diffusion Models for Imbalanced Text-to-Image Generation Training unbiased diffusion models from biased dataset

Reference 33

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PoGDiff: Product-of-Gaussians Diffusion Models for Imbalanced Text-to-Image Generation Fair generative modeling via weak supervision

Reference 34

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This paper cites Agedb: the first manually collected, in-the-wild age database.

PoGDiff: Product-of-Gaussians Diffusion Models for Imbalanced Text-to-Image Generation Agedb: the first manually collected, in-the-wild age database

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This paper cites Digiface-1m: 1 million digital face images for face recognition.

PoGDiff: Product-of-Gaussians Diffusion Models for Imbalanced Text-to-Image Generation Digiface-1m: 1 million digital face images for face recognition

Reference 36

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PoGDiff: Product-of-Gaussians Diffusion Models for Imbalanced Text-to-Image Generation Vggface2: A dataset for recognising faces across pose and age

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This paper cites Learning imbalanced datasets with label-distribution-aware margin loss.

PoGDiff: Product-of-Gaussians Diffusion Models for Imbalanced Text-to-Image Generation Learning imbalanced datasets with label-distribution-aware margin loss

Reference 38

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PoGDiff: Product-of-Gaussians Diffusion Models for Imbalanced Text-to-Image Generation GPT-4 Technical Report

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PoGDiff: Product-of-Gaussians Diffusion Models for Imbalanced Text-to-Image Generation Emerging properties in self-supervised vision transformers

Reference 40

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This paper cites Gans trained by a two time-scale update rule converge to a local nash equilibrium.

PoGDiff: Product-of-Gaussians Diffusion Models for Imbalanced Text-to-Image Generation Gans trained by a two time-scale update rule converge to a local nash equilibrium

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PoGDiff: Product-of-Gaussians Diffusion Models for Imbalanced Text-to-Image Generation Re- thinking the inception architecture for computer vision

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PoGDiff: Product-of-Gaussians Diffusion Models for Imbalanced Text-to-Image Generation Albert Einstein

Reference 43

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PoGDiff: Product-of-Gaussians Diffusion Models for Imbalanced Text-to-Image Generation Unresolved cited work

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PoGDiff: Product-of-Gaussians Diffusion Models for Imbalanced Text-to-Image Generation Limitations

Reference 45

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This paper cites Guidelines: • The answer NA means that the paper does not include theoretical results.

PoGDiff: Product-of-Gaussians Diffusion Models for Imbalanced Text-to-Image Generation Guidelines: • The answer NA means that the paper does not include theoretical results

Reference 46

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PoGDiff: Product-of-Gaussians Diffusion Models for Imbalanced Text-to-Image Generation Guidelines: • The answer NA means that the paper does not include experiments

Reference 47

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This paper cites For the code, we will release it once this paper is accepted.

PoGDiff: Product-of-Gaussians Diffusion Models for Imbalanced Text-to-Image Generation For the code, we will release it once this paper is accepted

Reference 48

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PoGDiff: Product-of-Gaussians Diffusion Models for Imbalanced Text-to-Image Generation Guidelines: • The answer NA means that the paper does not include experiments

Reference 49

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PoGDiff: Product-of-Gaussians Diffusion Models for Imbalanced Text-to-Image Generation Guidelines: • The answer NA means that the paper does not include experiments

Reference 50

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This paper cites Guidelines: • The answer NA means that the paper does not include experiments.

PoGDiff: Product-of-Gaussians Diffusion Models for Imbalanced Text-to-Image Generation Guidelines: • The answer NA means that the paper does not include experiments

Reference 51

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation a9b2df0f-132e-44cc-9d2d-5c4ef4b3a03f · outbound

This paper cites Guidelines: • The answer NA means that the authors have not reviewed the NeurIPS Code of Ethics.

PoGDiff: Product-of-Gaussians Diffusion Models for Imbalanced Text-to-Image Generation Guidelines: • The answer NA means that the authors have not reviewed the NeurIPS Code of Ethics

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T10:30:24.172215Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 72c35e5f-a3af-4c5b-9bf4-c4b42f4a18ee · outbound

This paper cites Guidelines: • The answer NA means that there is no societal impact of the work performed.

PoGDiff: Product-of-Gaussians Diffusion Models for Imbalanced Text-to-Image Generation Guidelines: • The answer NA means that there is no societal impact of the work performed

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T10:30:24.158845Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation cec628b8-4c67-42a8-b350-a6fb2cea8d60 · outbound

This paper cites Guidelines: • The answer NA means that the paper poses no such risks.

PoGDiff: Product-of-Gaussians Diffusion Models for Imbalanced Text-to-Image Generation Guidelines: • The answer NA means that the paper poses no such risks

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T10:30:24.144863Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation e4a7fe6d-084d-4f65-ba06-95c8e2fad841 · outbound

This paper cites Guidelines: • The answer NA means that the paper does not use existing assets.

PoGDiff: Product-of-Gaussians Diffusion Models for Imbalanced Text-to-Image Generation Guidelines: • The answer NA means that the paper does not use existing assets

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T10:30:24.131256Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 13f02526-3baa-4fdd-9eac-6d71aa8138a7 · outbound

This paper cites Guidelines: • The answer NA means that the paper does not release new assets.

PoGDiff: Product-of-Gaussians Diffusion Models for Imbalanced Text-to-Image Generation Guidelines: • The answer NA means that the paper does not release new assets

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T10:30:24.117892Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 78eb3a2b-000d-4ffc-bf2b-04af95b306c7 · outbound

This paper cites 29 Guidelines: • The answer NA means that the paper does not involve crowdsourcing nor research with human subjects.

PoGDiff: Product-of-Gaussians Diffusion Models for Imbalanced Text-to-Image Generation 29 Guidelines: • The answer NA means that the paper does not involve crowdsourcing nor research with human subjects

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T10:30:24.105147Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation a27c5724-a71d-4e9e-9ed8-f1655d8f8500 · outbound

This paper cites Guidelines: • The answer NA means that the paper does not involve crowdsourcing nor research with human subjects.

PoGDiff: Product-of-Gaussians Diffusion Models for Imbalanced Text-to-Image Generation Guidelines: • The answer NA means that the paper does not involve crowdsourcing nor research with human subjects

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T10:30:24.092284Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation e233f2df-d9ab-4849-8db3-423981c77c67 · outbound

This paper cites Answer: [NA] Justification: It is not applicable to our settings.

PoGDiff: Product-of-Gaussians Diffusion Models for Imbalanced Text-to-Image Generation Answer: [NA] Justification: It is not applicable to our settings

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T10:30:24.079224Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Pith citing papers

Observation a9c3f454-b6eb-439c-b697-e35793f40045 · inbound

A Comprehensive Survey on Imbalanced Data Learning cites this paper.

A Comprehensive Survey on Imbalanced Data Learning PoGDiff: Product-of-Gaussians Diffusion Models for Imbalanced Text-to-Image Generation

Reference 37

Resolution: verified exact; local_arxiv, observed 2026-08-07T23:07:20.225444Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.