Navigating Text-to-Image Generative Bias across Indic Languages

Agirre et al., E.: Semeval-2012 task 6: A pilot on semantic textual similarity*. In: International Workshop on Semantic Evaluation. pp. 7–8 (2012)

2012

Earlier work this paper cites.

Ramesh, A., Pavlov, M., Goh, G., Gray, S., Voss, C., Radford, A., Chen, M., Sutskever, I.: Zero-shot text-to-image generation. In: International Conference on Machine Learning. pp. 8821–8831. PMLR (2021)

2021

Earlier work this paper cites.

Costa-jussà et al., M.R.: No language left behind: Scaling human-centered machine translation. arXiv preprint arXiv:2207.04672 (2022)

Original

2022

Earlier work this paper cites.

Rombach, R., Blattmann, A., Lorenz, D., Esser, P., Ommer, B.: High-resolution image synthesis with latent diffusion models. In: Proceedings of the IEEE/CVF conference on computer vision and pattern recognition. pp. 10684–10695 (2022)

2022

Earlier work this paper cites.

Schuhmann, C., Beaumont, R., Vencu, R., Gordon, C., Wightman, R., Cherti, M., Coombes, T., Katta, A., Mullis, C., Wortsman, M., et al.: Laion-5b: An open large-scale dataset for training next generation image-text models. Advances in Neural Information Processing Systems 35

2022

Earlier work this paper cites.

Ahuja, K., Diddee, H., Hada, R., Ochieng, M., Ramesh, K., Jain, P., Nambi, A.U., Ganu, T., Segal, S., Ahmed, M., Bali, K., Sitaram, S.: MEGA: multilingual evaluation of generative AI. In: Conference on Empirical Methods in Natural Language Processing. pp. 4232–4267. Association for Computational Linguistics (2023)

2023

Earlier work this paper cites.

Chen, Z., Liu, G., Zhang, B., Yang, Q., Wu, L.: Altclip: Altering the language encoder in CLIP for extended language capabilities. In: Findings of the Association for Computational Linguistics: ACL. pp. 8666–8682. Association for Computational Linguistics (2023)

2023

Earlier work this paper cites.

Gala, J., Chitale, P.A., Raghavan, A.K., Gumma, V., Doddapaneni, S., M, A.K., Nawale, J.A., Sujatha, A., Puduppully, R., Raghavan, V., Kumar, P., Khapra, M.M., Dabre, R., Kunchukuttan, A.: Indictrans2: Towards high-quality and accessible machine translation models for all 22 scheduled indian languages. Transactions on Machine Learning Research (2023), https://openreview.net/forum?id=vfT4YuzAYA

2023

Cited alongside, same era.

Li, Y., Chang, C., Rawls, S., Vulic, I., Korhonen, A.: Translation-enhanced multilingual text-to-image generation. In: Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), ACL. pp. 9174–9193. Association for Computational Linguistics (2023)

2023

Cited alongside, same era.

Liu, B., Wang, L., Lyu, C., Zhang, Y., Su, J., Shi, S., Tu, Z.: On the cultural gap in text-to-image generation. arXiv preprint arXiv:2307.02971 (2023)

Original

2023

Cited alongside, same era.

Midjourney. https://www.midjourney.com/home (2024)

2024

Closest in time.

Chen, T., Hirota, Y., Otani, M., Garcia, N., Nakashima, Y.: Would deep generative models amplify bias in future models? In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. pp. 10833–10843 (2024)

2024

Closest in time.

Friedrich, F., Hämmerl, K., Schramowski, P., Libovicky, J., Kersting, K., Fraser, A.: Multilingual text-to-image generation magnifies gender stereotypes and prompt engineering may not help you. arXiv preprint arXiv:2401.16092 (2024)

Original

2024

Closest in time.

Govt. of India: Indian languages. https://www.education.gov.in/sites/upload_files/mhrd/files/upload_document/languagebr.pdf (2024)

2024

Closest in time.

OpenAI: Dalle3. https://openai.com/dall-e-3 (2024)

2024

Closest in time.