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Paper Citation Record · LEDGER

Inference Time Debiasing Concepts in Diffusion Models

As of 13 August 2026, this Paper Citation Record lists 24 of 24 outbound references and 0 inbound Pith citation observations for arXiv:2508.14933.

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

pith.paper-citation-record.v1
2508.14933 v1

Coverage vector

measured 24 of 24 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-05T18:47:20.828852Z

measured 24 of 24 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-13T06:32:02.005865+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 fuzzy8
  • unresolved14
  • parse uncertain0
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  • metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation fd283cc3-fb8e-4567-a46c-20c44b2d9414 · outbound

This paper cites Fairness and Bias in Multimodal AI: A Survey.

Inference Time Debiasing Concepts in Diffusion Models Fairness and Bias in Multimodal AI: A Survey

Reference 1

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Observation d33df5c7-2c60-499e-8160-ff9471afe922 · outbound

This paper cites an unresolved cited work.

Inference Time Debiasing Concepts in Diffusion Models Unresolved cited work

Reference 2

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Observation 4d3f001e-2807-41a6-853f-8396acd53cdd · outbound

This paper cites The Compute Divide in Machine Learning: A Threat to Academic Contribution and Scrutiny?.

Inference Time Debiasing Concepts in Diffusion Models The Compute Divide in Machine Learning: A Threat to Academic Contribution and Scrutiny?

Reference 3

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Observation 8160e8fa-0ae7-4cd1-97d8-4b3a3820f243 · outbound

This paper cites In: The 2024 ACM Conference on Fairness, Accountability, and Transparency.

Inference Time Debiasing Concepts in Diffusion Models In: The 2024 ACM Conference on Fairness, Accountability, and Transparency

Reference 4

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation c25df406-fb38-4e2f-8a22-88f89bd6ed9e · outbound

This paper cites Advances in Neural Information Processing Systems36, 25365–25389 (2023).

Inference Time Debiasing Concepts in Diffusion Models Advances in Neural Information Processing Systems36, 25365–25389 (2023)

Reference 5

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation f2221455-83d5-48e2-bb2a-fddab17712ce · outbound

This paper cites In: Proceedings of the IEEE/CVF In- ternational Conference on Computer Vision.

Inference Time Debiasing Concepts in Diffusion Models In: Proceedings of the IEEE/CVF In- ternational Conference on Computer Vision

Reference 6

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation 286b8344-3d9d-443a-ad9a-134e6d0fb139 · outbound

This paper cites In: International Conference on Machine Learning.

Inference Time Debiasing Concepts in Diffusion Models In: International Conference on Machine Learning

Reference 7

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No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation e3141330-998a-4caa-b0f6-ba9fe82ae2af · outbound

This paper cites CLIPScore: A Reference-free Evaluation Metric for Image Captioning.

Inference Time Debiasing Concepts in Diffusion Models CLIPScore: A Reference-free Evaluation Metric for Image Captioning

Reference 8

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Observation a528a91f-23cf-4145-897f-238cb429ef7d · outbound

This paper cites Classifier-Free Diffusion Guidance.

Inference Time Debiasing Concepts in Diffusion Models Classifier-Free Diffusion Guidance

Reference 9

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Observation 89e6a1b0-6a2a-490b-8a9f-089a3ed77e6e · outbound

This paper cites In: ACM Multi- media 2024 (2023).

Inference Time Debiasing Concepts in Diffusion Models In: ACM Multi- media 2024 (2023)

Reference 10

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation 24e2e53f-b187-4d69-95b1-ca861aceb3c2 · outbound

This paper cites T2ISafety: Benchmark for Assessing Fairness, Toxicity, and Privacy in Image Generation.

Inference Time Debiasing Concepts in Diffusion Models T2ISafety: Benchmark for Assessing Fairness, Toxicity, and Privacy in Image Generation

Reference 11

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Observation 7cc5b77e-00ab-488e-a489-172b95126887 · outbound

This paper cites In: Proceedings of International Conference on Computer Vision (ICCV) (December 2015).

Inference Time Debiasing Concepts in Diffusion Models In: Proceedings of International Conference on Computer Vision (ICCV) (December 2015)

Reference 12

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Unavailable: canonical work link unavailable.

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Observation 035723c3-287f-401a-bd6d-ac629247d0fa · outbound

This paper cites ACM computing surveys (CSUR)54(6), 1–35 (2021).

Inference Time Debiasing Concepts in Diffusion Models ACM computing surveys (CSUR)54(6), 1–35 (2021)

Reference 13

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Observation f3564647-7167-49c7-9c97-6c36a9f91023 · outbound

This paper cites Science366(6464), 447–453 (2019).

Inference Time Debiasing Concepts in Diffusion Models Science366(6464), 447–453 (2019)

Reference 14

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation e422949c-759c-4486-8114-ceacd2d77882 · outbound

This paper cites ACM Comput.

Inference Time Debiasing Concepts in Diffusion Models ACM Comput

Reference 15

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No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation 2daa4afc-8451-47e1-bdde-729fb1120e44 · outbound

This paper cites SDXL: Improving Latent Diffusion Models for High-Resolution Image Synthesis.

Inference Time Debiasing Concepts in Diffusion Models SDXL: Improving Latent Diffusion Models for High-Resolution Image Synthesis

Reference 16

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Observation 77998c7b-6179-4478-8661-e33c927af93b · outbound

This paper cites In: Proceedings of the 2020 conference on fairness, accountability, and transparency.

Inference Time Debiasing Concepts in Diffusion Models In: Proceedings of the 2020 conference on fairness, accountability, and transparency

Reference 17

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation 5fbe9517-609c-44e2-b2bd-83e4a7d4144f · outbound

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

Inference Time Debiasing Concepts in Diffusion Models In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition

Reference 18

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Observation 43af72db-905f-4b45-bd6a-33782115452d · outbound

This paper cites The Bias Amplification Paradox in Text-to-Image Generation.

Inference Time Debiasing Concepts in Diffusion Models The Bias Amplification Paradox in Text-to-Image Generation

Reference 19

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Observation 1ff30ec6-7c43-4582-ac1c-e13c1e02503a · outbound

This paper cites The Woman Worked as a Babysitter: On Biases in Language Generation.

Inference Time Debiasing Concepts in Diffusion Models The Woman Worked as a Babysitter: On Biases in Language Generation

Reference 20

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Observation a2d5d896-4aa0-4e6e-b32e-f13f9fa9961c · outbound

This paper cites Proceedings of the IEEE112(1), 4–11 (2024).

Inference Time Debiasing Concepts in Diffusion Models Proceedings of the IEEE112(1), 4–11 (2024)

Reference 21

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation d30f8017-0135-40de-976e-f75c85e03846 · outbound

This paper cites Mind 59(236), 433–460 (1950), http://www.jstor.org/stable/2251299.

Inference Time Debiasing Concepts in Diffusion Models Mind 59(236), 433–460 (1950), http://www.jstor.org/stable/2251299

Reference 22

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Observation 6da39ede-b95a-4213-959b-5bfd1185d728 · outbound

This paper cites Tackling the Generative Learning Trilemma with Denoising Diffusion GANs.

Inference Time Debiasing Concepts in Diffusion Models Tackling the Generative Learning Trilemma with Denoising Diffusion GANs

Reference 23

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Observation cb088919-f522-4817-83f8-defa5ada5a07 · outbound

This paper cites MIST: Mitigating Intersectional Bias with Disentangled Cross-Attention Editing in Text-to-Image Diffusion Models.

Inference Time Debiasing Concepts in Diffusion Models MIST: Mitigating Intersectional Bias with Disentangled Cross-Attention Editing in Text-to-Image Diffusion Models

Reference 24

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Unavailable: canonical work link unavailable.

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Pith citing papers

No inbound Pith citation observations are available.