Mishra, A., K. Alahari, and C. V. Jawahar (2012). Scene text recognition using higher order language priors. In BMVC.
Nichol, A., P. Dhariwal, A. Ramesh, P. Shyam, P. Mishkin, B. McGrew, I. Sutskever, and M. Chen (2022). Glide: Towards photorealistic image generation and editing with text-guided diffusion models.
Ortiz Suárez, P. J., L. Romary, and B. Sagot (2020, July). A monolingual approach to contextualized word embeddings for mid-resource languages. In Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, Online, pp. 1703-1714. Association for Computational Linguistics.
Ouyang, L., J. Wu, X. Jiang, D. Almeida, C. Wainwright, P. Mishkin, C. Zhang, S. Agarwal, K. Slama, A. Ray, J. Schulman, J. Hilton, F. Kelton, L. Miller, M. Simens, A. Askell, P. Welinder, P. F. Christiano, J. Leike, and R. Lowe (2022). Training language models to follow instructions with human feedback. In S. Koyejo, S. Mohamed, A. Agarwal, D. Belgrave, K. Cho, and A. Oh (Eds.), Advances in Neural Information Processing Systems, Volume 35, pp. 27730-27744. Curran Associates, Inc.
Piktus, A., C. Akiki, P. Villegas, H. Laurencon, G. Dupont, A. S. Luccioni, Y. Jernite, and A. Rogers (2023). The roots search tool: Data transparency for llms.
Radenovic, F., A. Dubey, A. Kadian, T. Mihaylov, S. Vandenhende, Y. Patel, Y. Wen, V. Ramanathan, and D. Mahajan (2023). Filtering, distillation, and hard negatives for vision-language pre-training.
Radford, A., J. W. Kim, C. Hallacy, A. Ramesh, G. Goh, S. Agarwal, G. Sastry, A. Askell, P. Mishkin, J. Clark, G. Krueger, and I. Sutskever (2021). Learning transferable visual models from natural language supervision. In International Conference on Machine Learning.
Rae, J. W., S. Borgeaud, T. Cai, K. Millican, J. Hoffmann, F. Song, J. Aslanides, S. Henderson, R. Ring, S. Young, E. Rutherford, T. Hennigan, J. Menick, A. Cassirer, R. Powell, G. van den Driessche, L. A. Hendricks, M. Rauh, P.-S. Huang, A. Glaese, J. Welbl, S. Dathathri, S. Huang, J. Uesato, J. Mellor, I. Higgins, A. Creswell, N. McAleese, A. Wu, E. Elsen, S. Jayakumar, E. Buchatskaya, D. Budden, E. Sutherland, K. Simonyan, M. Paganini, L. Sifre, L. Martens, X. L. Li, A. Kuncoro, A. Nematzadeh, E. Gribovskaya, D. Donato, A. Lazaridou, A. Mensch, J.-B. Lespiau, M. Tsimpoukelli, N. Grigorev, D. Fritz, T. Sottiaux, M. Pajarskas, T. Pohlen, Z. Gong, D. Toyama, C. de Masson d'Autume, Y. Li, T. Terzi, V. Mikulik, I. Babuschkin, A. Clark, D. de Las Casas, A. Guy, C. Jones, J. Bradbury, M. Johnson, B. Hechtman, L. Weidinger, I. Gabriel, W. Isaac, E. Lockhart, S. Osindero, L. Rimell, C. Dyer, O. Vinyals, K. Ayoub, J. Stanway, L. Bennett, D. Hassabis, K. Kavukcuoglu, and G. Irving (2022). Scaling language models: Methods, analysis & insights from training gopher.
Raffel, C., N. Shazeer, A. Roberts, K. Lee, S. Narang, M. Matena, Y. Zhou, W. Li, and P. J. Liu (2019). Exploring the limits of transfer learning with a unified text-to-text transformer. arXiv e-prints.
Ramesh, A., P. Dhariwal, A. Nichol, C. Chu, and M. Chen (2022). Hierarchical text-conditional image generation with clip latents.
Rombach, R., A. Blattmann, D. Lorenz, P. Esser, and B. Ommer (2021). High-resolution image synthesis with latent diffusion models.
Saharia, C., W. Chan, S. Saxena, L. Li, J. Whang, E. Denton, S. K. S. Ghasemipour, B. K. Ayan, S. S. Mahdavi, R. G. Lopes, T. Salimans, J. Ho, D. J. Fleet, and M. Norouzi (2022). Photorealistic text-to-image diffusion models with deep language understanding.
Schuhmann, C., R. Beaumont, R. Vencu, C. Gordon, R. Wightman, M. Cherti, T. Coombes, A. Katta, C. Mullis, M. Wortsman, P. Schramowski, S. Kundurthy, K. Crowson, L. Schmidt, R. Kaczmarczyk, and J. Jitsev (2022). Laion-5b: An open large-scale dataset for training next generation image-text models. In S. Koyejo, S. Mohamed, A. Agarwal, D. Belgrave,