mlsanityData to 7 Oct 2026

Gender Bias in Text-to-Video Generation Models: A case study of Sora

arXiv 2501.01987 ↗First posted 30 Dec 2024cs.CV cs.AI cs.CYcited by 8

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Abstract (arXiv)

The advent of text-to-video generation models has revolutionized content creation as it produces high-quality videos from textual prompts. However, concerns regarding inherent biases in such models have prompted scrutiny, particularly regarding gender representation. Our study investigates the presence of gender bias in OpenAI's Sora, a state-of-the-art text-to-video generation model. We uncover significant evidence of bias by analyzing the generated videos from a diverse set of gender-neutral and stereotypical prompts. The results indicate that Sora disproportionately associates specific genders with stereotypical behaviors and professions, which reflects societal prejudices embedded in its training data.

Key facts. Cited by 8 papers in the map (data through 7 Oct 2026). Builds on 12 of its 21 references that are in the map. First posted on arXiv 30 Dec 2024.

Builds on

12 of 21 references.

References · 12

  1. 2020StereoSet: Measuring stereotypical bias in pretrained language modelscited by 911
  2. 2023A Survey on Multimodal Large Language Modelscited by 898
  3. 2023Text2Video-Zero: Text-to-Image Diffusion Models are Zero-Shot Video Generatorscited by 666
  4. 2024Sora: A Review on Background, Technology, Limitations, and Opportunities of Large Vision Modelscited by 467
  5. 2021Persistent Anti-Muslim Bias in Large Language Modelscited by 376
  6. 2022DALL-Eval: Probing the Reasoning Skills and Social Biases of Text-to-Image Generation Modelscited by 230
  7. 2023A Survey on Video Diffusion Modelscited by 203
  8. 2023GenerateCT: Text-Conditional Generation of 3D Chest CT Volumescited by 64
  9. 2024Identifying Implicit Social Biases in Vision-Language Modelscited by 27
  10. 2023Survey of Social Bias in Vision-Language Modelscited by 26
  11. 2024Analyzing Quality, Bias, and Performance in Text-to-Image Generative Modelscited by 9
  12. 2024Negation Blindness in Large Language Models: Unveiling the NO Syndrome in Image Generationcited by 3

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2025: 5; 2026: 3.

8 papers.

  1. 2025Survey of Video Diffusion Models: Foundations, Implementations, and Applicationscited by 14
  2. 2025Debiasing CLIP: Interpreting and Correcting Bias in Attention Headscited by 4
  3. 2025Owls are wise and foxes are unfaithful: Uncovering animal stereotypes in vision-language modelscited by 1
  4. 2025Surgeons Are Indian Males and Speech Therapists Are White Females: Auditing Biases in Vision-Language Models for Healthcare Professionalscited by 1
  5. 2026FAIRT2V: Training-Free Debiasing for Text-to-Video Diffusion Modelscited by 1
  6. 2025A Multifaceted Analysis of Social Biases in Large Language Modelscited by 0
  7. 2026When to Lock Attention: Training-Free KV Control in Video Diffusioncited by 0
  8. 2026World Simulator: Queer Erotica and the Absurdity of AI Video Models That Promise the Worldcited by 0