Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-08T10:30:23.858263Z
Paper Citation Record · LEDGER
As of 8 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.
Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-08T10:30:23.858263Z
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-07T23:07:18.423091Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-07T23:07:20.219779Z
59 of 59 outbound references displayed
External citation measurements
No source-named external measurement is stored.
Observation 78ce380c-5e66-46cf-beb0-73d3d394fad6 · outbound
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
PoGDiff: Product-of-Gaussians Diffusion Models for Imbalanced Text-to-Image Generation Smote for regression
Reference 19
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Observation 8a063cfc-4c99-4358-a935-d20a75ffcb52 · outbound
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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Observation b95c5a7b-7ae8-41a3-8a08-305e970888ac · outbound
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
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
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
PoGDiff: Product-of-Gaussians Diffusion Models for Imbalanced Text-to-Image Generation RankSim: Ranking Similarity Regularization for Deep Imbalanced Regression
Reference 24
Source-reported events for the cited work
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Observation edb82222-04b2-40f5-b636-02064cf5799e · outbound
PoGDiff: Product-of-Gaussians Diffusion Models for Imbalanced Text-to-Image Generation ConR: Contrastive Regularizer for Deep Imbalanced Regression
Reference 25
Source-reported events for the cited work
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Observation 8848fcc9-b6f5-4e9e-bd8f-aed1161dd6c0 · outbound
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
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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Observation 008e8bd6-b6a6-462b-9f96-2453be4ea84e · outbound
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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Observation 8dc212d8-b281-40bb-a8b1-43250f3c232d · outbound
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
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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Observation 510a500e-3811-4754-b5d2-1d75abfff67d · outbound
PoGDiff: Product-of-Gaussians Diffusion Models for Imbalanced Text-to-Image Generation Label-Noise Robust Diffusion Models
Reference 31
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Observation ace67683-bb72-4b61-b956-232cb3f8cb8d · outbound
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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Observation 9841ea4d-7ebf-4333-8976-90820a8c5f36 · outbound
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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Observation 4c5a8b96-333b-47da-bfe2-2895e5d0802d · outbound
PoGDiff: Product-of-Gaussians Diffusion Models for Imbalanced Text-to-Image Generation Fair generative modeling via weak supervision
Reference 34
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Observation e1f1e3cb-805f-4e4c-9fa6-224d707b7bde · outbound
PoGDiff: Product-of-Gaussians Diffusion Models for Imbalanced Text-to-Image Generation Agedb: the first manually collected, in-the-wild age database
Reference 35
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Observation b00d4e5f-cd91-4086-b3c2-d8290afaf576 · outbound
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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Observation 1e2d9b4e-4255-4cab-99e5-f0e61faa3d97 · outbound
PoGDiff: Product-of-Gaussians Diffusion Models for Imbalanced Text-to-Image Generation Vggface2: A dataset for recognising faces across pose and age
Reference 37
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Observation 25a55335-e99f-4ca6-992e-89a57557213f · outbound
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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Observation f48ea55b-4189-4a86-906e-26f90fbbe9ba · outbound
PoGDiff: Product-of-Gaussians Diffusion Models for Imbalanced Text-to-Image Generation GPT-4 Technical Report
Reference 39
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Observation ed70e244-c968-43e7-ac44-8ad56a9c83cf · outbound
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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Observation 927eeb6a-59f5-4cb2-852d-3d94de08c44a · outbound
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
Reference 41
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Observation 758625af-df86-4972-91db-a9b0ec6def0c · outbound
PoGDiff: Product-of-Gaussians Diffusion Models for Imbalanced Text-to-Image Generation Re- thinking the inception architecture for computer vision
Reference 42
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Observation 5aa3033f-03ff-42a4-b68b-518ad981601e · outbound
PoGDiff: Product-of-Gaussians Diffusion Models for Imbalanced Text-to-Image Generation Albert Einstein
Reference 43
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Observation 8608ed23-6f93-439d-9802-2b89fb02c45a · outbound
PoGDiff: Product-of-Gaussians Diffusion Models for Imbalanced Text-to-Image Generation Unresolved cited work
Reference 44
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Observation 167ff142-56cb-4590-b79f-95dd29bb9560 · outbound
PoGDiff: Product-of-Gaussians Diffusion Models for Imbalanced Text-to-Image Generation Limitations
Reference 45
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Observation 42f08bf9-04e3-41b5-9080-c6d85f61bf35 · outbound
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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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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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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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
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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
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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
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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 use existing assets
Reference 55
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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 release new assets
Reference 56
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Observation 78eb3a2b-000d-4ffc-bf2b-04af95b306c7 · outbound
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
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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 involve crowdsourcing nor research with human subjects
Reference 58
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Observation e233f2df-d9ab-4849-8db3-423981c77c67 · outbound
PoGDiff: Product-of-Gaussians Diffusion Models for Imbalanced Text-to-Image Generation Answer: [NA] Justification: It is not applicable to our settings
Reference 59
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Observation a9c3f454-b6eb-439c-b697-e35793f40045 · inbound
A Comprehensive Survey on Imbalanced Data Learning PoGDiff: Product-of-Gaussians Diffusion Models for Imbalanced Text-to-Image Generation
Reference 37
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