Paper Citation Record · LEDGER

Contrastive Conditional-Unconditional Alignment for Long-tailed Diffusion Model

As of 9 August 2026, this Paper Citation Record lists 47 of 47 outbound references and 1 inbound Pith citation observation for arXiv:2507.09052.

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

pith.paper-citation-record.v1
2507.09052 v3

Coverage vector

measured 47 of 47 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T18:12:47.918260Z

measured 48 of 48 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-17T02:55:28.489534Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-17T02:58:55.093591Z

Reference resolution

47 of 47 outbound references displayed

verified exact0
verified fuzzy18
unresolved25
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 72e7a5ee-1b94-4de6-b735-78083742c291 · outbound

This paper cites In: International Conference on Artificial Intelligence and Statistics.

Contrastive Conditional-Unconditional Alignment for Long-tailed Diffusion Model In: International Conference on Artificial Intelligence and Statistics

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:12:52.182418Z

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Observation 37ac8200-9b03-43a2-b981-2f1251844155 · outbound

This paper cites Label-Efficient Semantic Segmentation with Diffusion Models.

Contrastive Conditional-Unconditional Alignment for Long-tailed Diffusion Model Label-Efficient Semantic Segmentation with Diffusion Models

Reference 2

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Observation 593118c8-9736-45f5-b227-2ac6f82707ba · outbound

This paper cites Demystifying MMD GANs.

Contrastive Conditional-Unconditional Alignment for Long-tailed Diffusion Model Demystifying MMD GANs

Reference 3

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Observation 6562ff80-7b31-4e74-b056-c845818b5a7b · outbound

This paper cites In: ICLR (2019).

Contrastive Conditional-Unconditional Alignment for Long-tailed Diffusion Model In: ICLR (2019)

Reference 4

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Observation 9629adbc-5114-4cb9-a324-a48da6e26a15 · outbound

This paper cites Advances in neural information processing systems32(2019).

Contrastive Conditional-Unconditional Alignment for Long-tailed Diffusion Model Advances in neural information processing systems32(2019)

Reference 5

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Observation 7116b5ee-08bd-4b21-a593-7aa728eb07a9 · outbound

This paper cites In: ICML (2020).

Contrastive Conditional-Unconditional Alignment for Long-tailed Diffusion Model In: ICML (2020)

Reference 6

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Observation 1682aab7-7b7a-4cf3-87a7-9f3a1a8147d7 · outbound

This paper cites DiffEdit: Diffusion-based semantic image editing with mask guidance.

Contrastive Conditional-Unconditional Alignment for Long-tailed Diffusion Model DiffEdit: Diffusion-based semantic image editing with mask guidance

Reference 7

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Observation 3650016c-30d6-4e58-b976-3a9709669990 · outbound

This paper cites In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition.

Contrastive Conditional-Unconditional Alignment for Long-tailed Diffusion Model In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition

Reference 8

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Observation 6a5ccb76-cf6d-4cda-8a26-b705d53be56c · outbound

This paper cites Advances in neural information processing systems34, 8780–8794 (2021).

Contrastive Conditional-Unconditional Alignment for Long-tailed Diffusion Model Advances in neural information processing systems34, 8780–8794 (2021)

Reference 9

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Observation c0d2da50-f0c3-420f-bf79-b2d836a60206 · outbound

This paper cites Diffusion Models and Representation Learning: A Survey.

Contrastive Conditional-Unconditional Alignment for Long-tailed Diffusion Model Diffusion Models and Representation Learning: A Survey

Reference 10

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Observation 63484a98-63fe-47c0-8531-2b16a2568273 · outbound

This paper cites In: CVPR (2020).

Contrastive Conditional-Unconditional Alignment for Long-tailed Diffusion Model In: CVPR (2020)

Reference 11

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Observation d228aa27-62cc-424f-a337-a60504080429 · outbound

This paper cites Imagen Video: High Definition Video Generation with Diffusion Models.

Contrastive Conditional-Unconditional Alignment for Long-tailed Diffusion Model Imagen Video: High Definition Video Generation with Diffusion Models

Reference 12

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Observation dd296832-460d-48e7-9e46-6842cf89f0c0 · outbound

This paper cites Advances in neural information processing systems33, 6840–6851 (2020).

Contrastive Conditional-Unconditional Alignment for Long-tailed Diffusion Model Advances in neural information processing systems33, 6840–6851 (2020)

Reference 13

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Observation f9722345-a06a-498c-9f13-446cf135caf8 · outbound

This paper cites Classifier-Free Diffusion Guidance.

Contrastive Conditional-Unconditional Alignment for Long-tailed Diffusion Model Classifier-Free Diffusion Guidance

Reference 14

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Observation 0a12160b-539c-4172-bb24-7bcc58f66d48 · outbound

This paper cites Advances in Neural Information Processing Systems35, 8633–8646 (2022).

Contrastive Conditional-Unconditional Alignment for Long-tailed Diffusion Model Advances in Neural Information Processing Systems35, 8633–8646 (2022)

Reference 15

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Observation cd1e7302-7937-4761-8cd8-040d5a56df5c · outbound

This paper cites In: ICML (2021).

Contrastive Conditional-Unconditional Alignment for Long-tailed Diffusion Model In: ICML (2021)

Reference 16

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Observation 1d5fa811-da14-490c-98a1-e78bc9bafa32 · outbound

This paper cites Advances in neural information processing systems33, 12104–12114 (2020).

Contrastive Conditional-Unconditional Alignment for Long-tailed Diffusion Model Advances in neural information processing systems33, 12104–12114 (2020)

Reference 17

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Observation 16b84460-37b0-46f1-8537-fa66039d6835 · outbound

This paper cites In: CVPR (2019).

Contrastive Conditional-Unconditional Alignment for Long-tailed Diffusion Model In: CVPR (2019)

Reference 18

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This paper cites In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition.

Contrastive Conditional-Unconditional Alignment for Long-tailed Diffusion Model In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition

Reference 19

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Observation 75a7b507-2e3c-4343-84cd-0d00932dcfca · outbound

This paper cites In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition.

Contrastive Conditional-Unconditional Alignment for Long-tailed Diffusion Model In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition

Reference 20

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Observation b9d2edc4-87d4-488c-82d9-274ce3f6e876 · outbound

This paper cites Advances in neural information processing systems33, 18661–18673 (2020).

Contrastive Conditional-Unconditional Alignment for Long-tailed Diffusion Model Advances in neural information processing systems33, 18661–18673 (2020)

Reference 21

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Observation c27eb952-3032-49d2-a400-d30e055c9cef · outbound

This paper cites Foundations and Trends®in Machine Learning12(4), 307–392 (2019).

Contrastive Conditional-Unconditional Alignment for Long-tailed Diffusion Model Foundations and Trends®in Machine Learning12(4), 307–392 (2019)

Reference 22

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Observation f931e64a-7e6b-42ab-8d32-1bf60aedb58b · outbound

This paper cites In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition.

Contrastive Conditional-Unconditional Alignment for Long-tailed Diffusion Model In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition

Reference 23

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Observation 3eeb151e-42ca-4525-95fe-87985b4bb897 · outbound

This paper cites IEEE Transactions on Pattern Analysis and Machine Intelligence (2022).

Contrastive Conditional-Unconditional Alignment for Long-tailed Diffusion Model IEEE Transactions on Pattern Analysis and Machine Intelligence (2022)

Reference 24

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Observation e052e1e0-3648-44fe-97ea-08c4b1052656 · outbound

This paper cites In: European Conference on Computer Vision.

Contrastive Conditional-Unconditional Alignment for Long-tailed Diffusion Model In: European Conference on Computer Vision

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This paper cites Journal of machine learning research9(11) (2008).

Contrastive Conditional-Unconditional Alignment for Long-tailed Diffusion Model Journal of machine learning research9(11) (2008)

Reference 26

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This paper cites Representation Learning with Contrastive Predictive Coding.

Contrastive Conditional-Unconditional Alignment for Long-tailed Diffusion Model Representation Learning with Contrastive Predictive Coding

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Contrastive Conditional-Unconditional Alignment for Long-tailed Diffusion Model In: International Conference on Machine Learn- ing

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Observation 49efc78b-654f-4a76-9e70-f33e88524766 · outbound

This paper cites arXiv (2022).

Contrastive Conditional-Unconditional Alignment for Long-tailed Diffusion Model arXiv (2022)

Reference 29

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Observation beebc0d6-9deb-4c95-8d14-625384f13378 · outbound

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Contrastive Conditional-Unconditional Alignment for Long-tailed Diffusion Model In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition

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Contrastive Conditional-Unconditional Alignment for Long-tailed Diffusion Model In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recog- nition

Reference 31

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Observation 76a8fdcf-bb78-4771-861f-45a3d19b027d · outbound

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Contrastive Conditional-Unconditional Alignment for Long-tailed Diffusion Model In: European Conference on Computer Vision

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Contrastive Conditional-Unconditional Alignment for Long-tailed Diffusion Model In: Proceedings of the IEEE/CVF conference on computer vision and pattern recognition

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Contrastive Conditional-Unconditional Alignment for Long-tailed Diffusion Model In: Proceedings of the IEEE/CVF conference on computer vision and pattern recognition

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Contrastive Conditional-Unconditional Alignment for Long-tailed Diffusion Model In: International Confer- ence on Learning Representations (2022),https://openreview.net/forum?id= 7TZeCsNOUB_ CCUA: Long-tailed Diffusion Models Training 17

Reference 35

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Contrastive Conditional-Unconditional Alignment for Long-tailed Diffusion Model In: Proceed- ings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition

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Contrastive Conditional-Unconditional Alignment for Long-tailed Diffusion Model Denoising Diffusion Implicit Models

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Contrastive Conditional-Unconditional Alignment for Long-tailed Diffusion Model In: Proceedings of the IEEE conference on computer vision and pattern recognition

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This paper cites Improving the Fairness of Deep Generative Models without Retraining.

Contrastive Conditional-Unconditional Alignment for Long-tailed Diffusion Model Improving the Fairness of Deep Generative Models without Retraining

Reference 40

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Contrastive Conditional-Unconditional Alignment for Long-tailed Diffusion Model Diffuse and Disperse: Image Generation with Representation Regularization

Reference 41

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Contrastive Conditional-Unconditional Alignment for Long-tailed Diffusion Model Analysis of Classifier-Free Guidance Weight Schedulers

Reference 42

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Contrastive Conditional-Unconditional Alignment for Long-tailed Diffusion Model Training Class-Imbalanced Diffusion Model Via Overlap Optimization

Reference 43

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Contrastive Conditional-Unconditional Alignment for Long-tailed Diffusion Model Representation Alignment for Generation: Training Diffusion Transformers Is Easier Than You Think

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Contrastive Conditional-Unconditional Alignment for Long-tailed Diffusion Model To Balance or Not to Balance: A Simple-yet-Effective Approach for Learning with Long-Tailed Distributions

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Contrastive Conditional-Unconditional Alignment for Long-tailed Diffusion Model In: Proceedings of the IEEE/CVF International Conference on Computer Vision

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Contrastive Conditional-Unconditional Alignment for Long-tailed Diffusion Model In: The Twelfth International Conference on Learning Representations (2024) 18 Fang et al

Reference 47

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Pith citing papers

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GRASP: Guided Residual Adapters with Sample-wise Partitioning cites this paper.

GRASP: Guided Residual Adapters with Sample-wise Partitioning Contrastive Conditional-Unconditional Alignment for Long-tailed Diffusion Model

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