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Paper Citation Record · LEDGER

Bias Analysis in Unconditional Image Generative Models

As of 17 August 2026, this Paper Citation Record lists 59 of 59 outbound references and 0 inbound Pith citation observations for arXiv:2506.09106.

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

pith.paper-citation-record.v1
2506.09106 v1

Coverage vector

measured 59 of 59 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T05:03:52.772808Z

measured 59 of 59 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

59 of 59 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation d080fa54-e1fc-460d-b302-41b86788291d · outbound

This paper cites LLaMA: Open and Efficient Foundation Language Models.

Bias Analysis in Unconditional Image Generative Models LLaMA: Open and Efficient Foundation Language Models

Reference 1

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Observation c0cd3631-4fc8-47e7-ae41-80b5c2523d2a · outbound

This paper cites GPT-4 Technical Report.

Bias Analysis in Unconditional Image Generative Models GPT-4 Technical Report

Reference 2

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Observation a6932a01-17bd-4d60-854c-791e1137ea76 · outbound

This paper cites Hierarchical Text-Conditional Image Generation with CLIP Latents.

Bias Analysis in Unconditional Image Generative Models Hierarchical Text-Conditional Image Generation with CLIP Latents

Reference 3

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Observation d90dffe0-f5be-4b9e-8d20-fdd00cd90210 · outbound

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

Bias Analysis in Unconditional Image Generative Models High-resolution image synthesis with latent diffusion models

Reference 4

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Observation 2ea88e61-c8c7-4ffd-896d-4bac80aec153 · outbound

This paper cites Scaling rectified flow transformers for high-resolution im- age synthesis.

Bias Analysis in Unconditional Image Generative Models Scaling rectified flow transformers for high-resolution im- age synthesis

Reference 5

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Observation 6d5307c7-12bf-4565-ad4e-9fcdc1b02b66 · outbound

This paper cites Audiogen: Textually guided audio generation.

Bias Analysis in Unconditional Image Generative Models Audiogen: Textually guided audio generation

Reference 6

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Observation 9a91de34-9229-409d-b139-2b32df4c9ddf · outbound

This paper cites Gritsenko, William Chan, Mohammad Norouzi, and David J.

Bias Analysis in Unconditional Image Generative Models Gritsenko, William Chan, Mohammad Norouzi, and David J

Reference 7

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Observation ae6dc1a7-5cc9-4959-9825-769cb1614e50 · outbound

This paper cites Make- a-video: Text-to-video generation without text-video data.

Bias Analysis in Unconditional Image Generative Models Make- a-video: Text-to-video generation without text-video data

Reference 8

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Observation 1a98f323-ce62-4e7d-88eb-679bdd57ce23 · outbound

This paper cites Which ai image generator is the most biased?, 2023.

Bias Analysis in Unconditional Image Generative Models Which ai image generator is the most biased?, 2023

Reference 9

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Observation bdd163c5-005c-4d16-a918-e402b3673016 · outbound

This paper cites These fake images reveal how ai amplifies our worst stereotypes, 2023.

Bias Analysis in Unconditional Image Generative Models These fake images reveal how ai amplifies our worst stereotypes, 2023

Reference 10

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Observation a23ed419-3a47-4765-8577-be3986256be9 · outbound

This paper cites Zero-shot text-to-image generation.

Bias Analysis in Unconditional Image Generative Models Zero-shot text-to-image generation

Reference 11

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Observation 3ba38560-390c-40ee-8337-b8d2d5f80a76 · outbound

This paper cites DALL-EV AL: probing the reasoning skills and social biases of text-to-image generation models.

Bias Analysis in Unconditional Image Generative Models DALL-EV AL: probing the reasoning skills and social biases of text-to-image generation models

Reference 12

Resolution
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Observation 0ad3bf8e-e8a0-48ca-8c4a-2523cd2a7ab0 · outbound

This paper cites Easily accessible text-to-image generation amplifies demographic stereotypes at large scale.

Bias Analysis in Unconditional Image Generative Models Easily accessible text-to-image generation amplifies demographic stereotypes at large scale

Reference 13

Resolution
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Observation 95618af5-c41c-478b-a169-73d3fa0a20e5 · outbound

This paper cites Stable bias: Eval- uating societal representations in diffusion models.

Bias Analysis in Unconditional Image Generative Models Stable bias: Eval- uating societal representations in diffusion models

Reference 14

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Observation 61509f32-c96d-472b-8e2a-b6bdac86e582 · outbound

This paper cites Auditing and instructing text-to-image generation mod- els on fairness.

Bias Analysis in Unconditional Image Generative Models Auditing and instructing text-to-image generation mod- els on fairness

Reference 15

Resolution
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Source-reported events for the cited work

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Observation 99997f5a-7e47-4433-8417-a089fdfe2ed3 · outbound

This paper cites The bias amplification paradox in text- to-image generation.

Bias Analysis in Unconditional Image Generative Models The bias amplification paradox in text- to-image generation

Reference 16

Resolution
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Observation e34ed411-f108-413e-a4cb-36fab3fc629f · outbound

This paper cites Analyzing bias in diffusion-based face generation mod- els.

Bias Analysis in Unconditional Image Generative Models Analyzing bias in diffusion-based face generation mod- els

Reference 17

Resolution
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Observation c15c1161-0f05-47e8-acd7-fca4b0018560 · outbound

This paper cites LAION-5B: an open large-scale dataset for training next generation image-text models.

Bias Analysis in Unconditional Image Generative Models LAION-5B: an open large-scale dataset for training next generation image-text models

Reference 18

Resolution
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Source-reported events for the cited work

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Observation e2bf82cf-9435-4aff-ab54-b0d27c3854e1 · outbound

This paper cites Denoising diffusion probabilistic models.

Bias Analysis in Unconditional Image Generative Models Denoising diffusion probabilistic models

Reference 19

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Source-reported events for the cited work

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Observation 27d5b1a6-bde7-450b-8b84-396f5bd67985 · outbound

This paper cites Generative modeling by estimating gradients of the data dis- tribution.

Bias Analysis in Unconditional Image Generative Models Generative modeling by estimating gradients of the data dis- tribution

Reference 20

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Observation cc41af28-613e-4e45-8a00-8b6024c41d11 · outbound

This paper cites Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron C.

Bias Analysis in Unconditional Image Generative Models Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron C

Reference 21

Resolution
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Observation 5b432fbf-a0a9-4288-a62a-9ddf498a5f32 · outbound

This paper cites Large scale GAN training for high fidelity natural image synthesis.

Bias Analysis in Unconditional Image Generative Models Large scale GAN training for high fidelity natural image synthesis

Reference 22

Resolution
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Observation c6ead141-213c-4542-b26b-8ef22afbcf05 · outbound

This paper cites Classifier-Free Diffusion Guidance.

Bias Analysis in Unconditional Image Generative Models Classifier-Free Diffusion Guidance

Reference 23

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Source-reported events for the cited work

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Observation 3bb3c8a8-f2aa-442d-b607-9f8a68a5187f · outbound

This paper cites Guiding a diffusion model with a bad version of itself.

Bias Analysis in Unconditional Image Generative Models Guiding a diffusion model with a bad version of itself

Reference 24

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Source-reported events for the cited work

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Observation febcf871-c0d0-40d5-9ff5-71cf81651b66 · outbound

This paper cites A brief review on algorithmic fairness.

Bias Analysis in Unconditional Image Generative Models A brief review on algorithmic fairness

Reference 25

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Observation e37df626-75f8-41f3-bf64-05dfca204a55 · outbound

This paper cites Finetuning text-to-image diffusion models for fairness.

Bias Analysis in Unconditional Image Generative Models Finetuning text-to-image diffusion models for fairness

Reference 26

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Source-reported events for the cited work

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Observation d01e7161-9098-4699-b724-56830656c73f · outbound

This paper cites On Fairness of Unified Multimodal Large Language Model for Image Generation.

Bias Analysis in Unconditional Image Generative Models On Fairness of Unified Multimodal Large Language Model for Image Generation

Reference 27

Resolution
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Observation e282bd30-fb08-48e9-a444-19dffb60d36e · outbound

This paper cites Deep learning face attributes in the wild.

Bias Analysis in Unconditional Image Generative Models Deep learning face attributes in the wild

Reference 28

Resolution
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Source-reported events for the cited work

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Observation f3ff7ba4-a32f-4266-a1b3-fe932835ffa4 · outbound

This paper cites Deepfashion: Powering robust clothes recognition and retrieval with rich annotations.

Bias Analysis in Unconditional Image Generative Models Deepfashion: Powering robust clothes recognition and retrieval with rich annotations

Reference 29

Resolution
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Observation 4c4cccc8-1c64-4882-873e-cee262d0c9b8 · outbound

This paper cites mindall-e on conceptual captions.

Bias Analysis in Unconditional Image Generative Models mindall-e on conceptual captions

Reference 30

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Source-reported events for the cited work

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Observation e52962d9-36e0-496b-8c0d-2ad9ec6bb30e · outbound

This paper cites Karlo-v1.0.alpha on coyo-100m and cc15m.

Bias Analysis in Unconditional Image Generative Models Karlo-v1.0.alpha on coyo-100m and cc15m

Reference 31

Resolution
verified fuzzy
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Source-reported events for the cited work

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Observation 06ddafd0-ba37-4af2-8fe2-c31c8715b507 · outbound

This paper cites Learning transferable visual models from natural language supervision.

Bias Analysis in Unconditional Image Generative Models Learning transferable visual models from natural language supervision

Reference 32

Resolution
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Source-reported events for the cited work

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Observation afeb9cc2-51a0-4fd6-aa93-bd7f4617150f · outbound

This paper cites an unresolved cited work.

Bias Analysis in Unconditional Image Generative Models Unresolved cited work

Reference 33

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Source-reported events for the cited work

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Observation 3311b414-f7a6-4b88-b851-f120de283fed · outbound

This paper cites An image is worth 16x16 words: Transformers for image recognition at scale.

Bias Analysis in Unconditional Image Generative Models An image is worth 16x16 words: Transformers for image recognition at scale

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:03:55.825883Z

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.

source=pdf_text observed=2026-08-07T05:03:51.203242Z digest=sha256:e670064b5e371cfbe58d52600382bc635553985bec0978dc5649ac041dfb9efb

Observation 9ad91b6a-ead2-46f6-b9d3-bac703042159 · outbound

This paper cites On the Opportunities and Risks of Foundation Models.

Bias Analysis in Unconditional Image Generative Models On the Opportunities and Risks of Foundation Models

Reference 35

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-07T05:03:51.254810Z digest=sha256:ca225739967f85a176ccbc60c0f59df31872e2a0a7e87a42d0cedf73c36043cb

Observation 65efc815-def5-47b3-bd8e-58b859ec1c98 · outbound

This paper cites CLIP the bias: How useful is balancing data in multimodal learning? In The Twelfth International Conference on Learning Representations.

Bias Analysis in Unconditional Image Generative Models CLIP the bias: How useful is balancing data in multimodal learning? In The Twelfth International Conference on Learning Representations

Reference 36

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verified fuzzy
raw_fallback, observed 2026-08-07T05:03:55.715259Z

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.

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Observation 8049fe52-0ae1-45b8-8596-f3baea646aaa · outbound

This paper cites Fairness definitions explained.

Bias Analysis in Unconditional Image Generative Models Fairness definitions explained

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:03:55.573875Z

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.

source=pdf_text observed=2026-08-07T05:03:51.352387Z digest=sha256:b090bd65db4638f4658e18261b907e59bdc40c8df94c164dc4f4aedfc43776d9

Observation 76e7dddb-8611-49d8-a0e4-de829ec47171 · outbound

This paper cites an unresolved cited work.

Bias Analysis in Unconditional Image Generative Models Unresolved cited work

Reference 38

Resolution
unresolved
raw_fallback, observed 2026-08-07T05:03:55.448307Z

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.

source=pdf_text observed=2026-08-07T05:03:51.417802Z digest=sha256:fd0b0b22e814c35d5bf76101b554c52d02423a5a4ca1c9c514fdab59620335f4

Observation 80e5e66d-1b92-4176-8813-4814cea9a292 · outbound

This paper cites Diffusion models beat gans on image synthe- sis.

Bias Analysis in Unconditional Image Generative Models Diffusion models beat gans on image synthe- sis

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:03:55.295833Z

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.

source=pdf_text observed=2026-08-07T05:03:51.466623Z digest=sha256:ef385e12d59aa68243d3aa4d6a52f1fc574513a41fe44646a6f46951578309a8

Observation 9066b014-ed6a-42e9-873a-42039d567626 · outbound

This paper cites U-net: Convolutional networks for biomedical image segmentation.

Bias Analysis in Unconditional Image Generative Models U-net: Convolutional networks for biomedical image segmentation

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:03:55.184878Z

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.

source=pdf_text observed=2026-08-07T05:03:51.524972Z digest=sha256:435af3e968dad21277e4267b9a063fefa9794e392b2055d34251a6d494174798

Observation 1014477b-a86b-4f4a-b82a-35207457f56a · outbound

This paper cites Girshick, Piotr Doll ´ar, Zhuowen Tu, and Kaiming He.

Bias Analysis in Unconditional Image Generative Models Girshick, Piotr Doll ´ar, Zhuowen Tu, and Kaiming He

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:03:55.083685Z

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.

source=pdf_text observed=2026-08-07T05:03:51.586228Z digest=sha256:7e1b7e19b3b849de4f53a873fe18f9279c6dc876586deaf4a0eda291f8d5ac3e

Observation 40147fa7-e87b-4b8f-aba3-375b1cec90a1 · outbound

This paper cites Swin transformer: Hierarchical vision transformer using shifted windows.

Bias Analysis in Unconditional Image Generative Models Swin transformer: Hierarchical vision transformer using shifted windows

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:03:54.970343Z

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.

source=pdf_text observed=2026-08-07T05:03:51.662943Z digest=sha256:6868414ad5b8e57d7b54f441d4ccc29725f55dc744033fb67f8f31f0c7e48e25

Observation 94d31a75-6632-4d0e-87cc-0552c65e48cf · outbound

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

Bias Analysis in Unconditional Image Generative Models Gans trained by a two time-scale update rule converge to a local nash equilibrium

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:03:54.821912Z

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.

source=pdf_text observed=2026-08-07T05:03:51.742449Z digest=sha256:dddaed34d1642dc2e14dfe345e233fcbf426258bd52d86ec34b3c43d4149b356

Observation c81deaa3-334d-4b29-90db-06bb0cc68bb8 · outbound

This paper cites Sutherland, Michael Arbel, and Arthur Gretton.

Bias Analysis in Unconditional Image Generative Models Sutherland, Michael Arbel, and Arthur Gretton

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:03:54.725739Z

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.

source=pdf_text observed=2026-08-07T05:03:51.800857Z digest=sha256:128d5db7988e2d900717f34b9450b9ec767272916974e38c4d34a799cd1f12f6

Observation 84d6ba0c-bbfc-4f1f-b453-fa2b1ca36760 · outbound

This paper cites Feature likelihood score: Evaluating the generalization of generative models using samples.

Bias Analysis in Unconditional Image Generative Models Feature likelihood score: Evaluating the generalization of generative models using samples

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:03:54.617306Z

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.

source=pdf_text observed=2026-08-07T05:03:51.881881Z digest=sha256:d06232e207f6c59498f2515d89ed54989521556ddb5f7ca1799152591106e95c

Observation a565162c-9bf4-49fb-ab58-8d532fad80df · outbound

This paper cites an unresolved cited work.

Bias Analysis in Unconditional Image Generative Models Unresolved cited work

Reference 46

Resolution
unresolved
raw_fallback, observed 2026-08-07T05:03:54.475079Z

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.

source=pdf_text observed=2026-08-07T05:03:51.946993Z digest=sha256:2c252327279996af5afc2ac826c7c382cddbe29a8926a5c9919b4a2b2dbad888

Observation 7422b46e-6999-4d54-bab3-1a0f667aac03 · outbound

This paper cites an unresolved cited work.

Bias Analysis in Unconditional Image Generative Models Unresolved cited work

Reference 47

Resolution
unresolved
raw_fallback, observed 2026-08-07T05:03:54.331214Z

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.

source=pdf_text observed=2026-08-07T05:03:52.008901Z digest=sha256:7d8103ea415bdad68824b15915af1e90c48c058bbc605c07b6191ce99cccad00

Observation 87354cbd-c21e-4ee0-be36-8ccd9e6ba6c7 · outbound

This paper cites Wasserstein generative adversarial net- works.

Bias Analysis in Unconditional Image Generative Models Wasserstein generative adversarial net- works

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:03:54.188006Z

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.

source=pdf_text observed=2026-08-07T05:03:52.064664Z digest=sha256:d339501caefa7c46058c5d51cd8c6bdf6a63d0f16b0cbb3fea2e8fefac4a249d

Observation 77b6b737-3e2c-4cb5-a07c-385cf0049fad · outbound

This paper cites Big data’s disparate impact.

Bias Analysis in Unconditional Image Generative Models Big data’s disparate impact

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:03:54.070050Z

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.

source=pdf_text observed=2026-08-07T05:03:52.138794Z digest=sha256:7bf3bdbcae66cc52a69ca2490f6fc841c799206f138337dddcc6f9760348138b

Observation da0d2491-cdb5-46f4-8622-561569b1bac7 · outbound

This paper cites Gender shades: Intersectional accuracy disparities in commercial gender classification.

Bias Analysis in Unconditional Image Generative Models Gender shades: Intersectional accuracy disparities in commercial gender classification

Reference 50

Resolution
unresolved
no resolver link, observed 2026-08-07T05:03:52.204826Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:03:52.204826Z digest=sha256:707963e25d5e199a17d48efc25e7d779d18c7f1d31d6204621ba105387b588f0

Observation a9e80876-1bfc-4388-9ceb-f44bb9cbdfdc · outbound

This paper cites Actionable auditing: Investigating the impact of publicly naming biased performance results of commercial ai products.AAAI/ACM Conference on AI, Ethics, and Society, 2019.

Bias Analysis in Unconditional Image Generative Models Actionable auditing: Investigating the impact of publicly naming biased performance results of commercial ai products.AAAI/ACM Conference on AI, Ethics, and Society, 2019

Reference 51

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:03:53.949638Z

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.

source=pdf_text observed=2026-08-07T05:03:52.268925Z digest=sha256:9a5e81e51d579f21a5787a8bbf5853b7bdaf904c69cbeb5a172dd1fa39916087

Observation baf5b323-e764-4ded-83ea-ffe1470e7a3e · outbound

This paper cites Auditing al- gorithms: Research methods for detecting discrimination on internet platforms.

Bias Analysis in Unconditional Image Generative Models Auditing al- gorithms: Research methods for detecting discrimination on internet platforms

Reference 52

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:03:53.825925Z

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.

source=pdf_text observed=2026-08-07T05:03:52.338364Z digest=sha256:2e558d9a4c55f94e7408b60320fc261a5d370fcdbedfb65a98be44f4660bdead

Observation 110b5182-0982-491b-b9bb-391c114881ce · outbound

This paper cites Paul, and Jed R.

Bias Analysis in Unconditional Image Generative Models Paul, and Jed R

Reference 53

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:03:53.709967Z

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.

source=pdf_text observed=2026-08-07T05:03:52.402384Z digest=sha256:451245346013605d47858ad7e77898d4e5793f1a0dbdc8130186f5b226523ab6

Observation 84f7e0f7-7833-4b59-b3f0-9a5000f0759a · outbound

This paper cites Datasheets for datasets, 2021.

Bias Analysis in Unconditional Image Generative Models Datasheets for datasets, 2021

Reference 54

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:03:53.588675Z

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.

source=pdf_text observed=2026-08-07T05:03:52.463143Z digest=sha256:7a98d93da00bdde689ec3a06fb5f7237b8c1fc23e4c6b669c867eb8753103c70

Observation cbc14219-cddb-432c-ab5a-b313594e240e · outbound

This paper cites Improved denoising diffusion probabilistic models.

Bias Analysis in Unconditional Image Generative Models Improved denoising diffusion probabilistic models

Reference 55

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:03:53.454996Z

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.

source=pdf_text observed=2026-08-07T05:03:52.516866Z digest=sha256:0cdaae5836f023adbcf74df8987ff929fb34bc0b37a291757e2c9dc397d392fc

Observation 5a0b0c42-71b9-4643-ac10-a38730c3c157 · outbound

This paper cites Denoising diffusion implicit models.

Bias Analysis in Unconditional Image Generative Models Denoising diffusion implicit models

Reference 56

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:03:53.316808Z

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.

source=pdf_text observed=2026-08-07T05:03:52.572078Z digest=sha256:eeef665918f1a3a8de27fe8bdaaa7e8270d42e43c34e470d828c5f480bcb7609

Observation 95ecc1dd-d11f-4576-8c53-a7c397f357f8 · outbound

This paper cites Men also like shopping: Reducing gender bias amplification using corpus-level constraints.

Bias Analysis in Unconditional Image Generative Models Men also like shopping: Reducing gender bias amplification using corpus-level constraints

Reference 57

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:03:53.215221Z

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.

source=pdf_text observed=2026-08-07T05:03:52.656094Z digest=sha256:b7c89da90a1da293e4b6fc025cf3e503eff9bed7c28fc72ee6d5dd50496c0778

Observation 4b0bf9a9-da8d-445e-a7b1-b7f337e625d2 · outbound

This paper cites A Systematic Study of Bias Amplification.

Bias Analysis in Unconditional Image Generative Models A Systematic Study of Bias Amplification

Reference 58

Resolution
unresolved
no resolver link, observed 2026-08-07T05:03:52.705323Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:03:52.705323Z digest=sha256:7381afcd3536eb7717e06dd0c43a38d30b5c49d05a42571c88eb972a8dda0f32

Observation c767686b-af06-49d2-8202-3d8c913cd3ef · outbound

This paper cites Consistency and accuracy of celeba attribute values.

Bias Analysis in Unconditional Image Generative Models Consistency and accuracy of celeba attribute values

Reference 59

Resolution
malformed identifier
raw_fallback, observed 2026-08-07T05:03:53.108806Z

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.

source=pdf_text observed=2026-08-07T05:03:52.772808Z digest=sha256:0dbf4361ea1bb6e6bb4b8bd5489cefa5da3be9f63a8c301673b19dbabf4a0d6e

Pith citing papers

No inbound Pith citation observations are available.