Bias Analysis in Unconditional Image Generative Models | Paper Citation Record

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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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This paper cites GPT-4 Technical Report.

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

Reference 2

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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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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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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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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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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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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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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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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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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

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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

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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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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

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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

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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

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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

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This paper cites Denoising diffusion probabilistic models.

Bias Analysis in Unconditional Image Generative Models Denoising diffusion probabilistic models

Reference 19

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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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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

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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

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This paper cites Classifier-Free Diffusion Guidance.

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

Reference 23

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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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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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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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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

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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

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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

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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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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

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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

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Bias Analysis in Unconditional Image Generative Models Unresolved cited work

Reference 33

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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

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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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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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This paper cites Fairness definitions explained.

Bias Analysis in Unconditional Image Generative Models Fairness definitions explained

Reference 37

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Bias Analysis in Unconditional Image Generative Models Unresolved cited work

Reference 38

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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

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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

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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

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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

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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

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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

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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

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Bias Analysis in Unconditional Image Generative Models Unresolved cited work

Reference 46

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Bias Analysis in Unconditional Image Generative Models Unresolved cited work

Reference 47

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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

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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

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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

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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

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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

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This paper cites Paul, and Jed R.

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

Reference 53

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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

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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

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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

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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

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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

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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

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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