Latent Guard: a Safety Framework for Text-to-image Generation

van der Maaten, L., Hinton, G.: Visualizing data using t-sne. JMLR (2008)

2008

Earlier work this paper cites.

Lin, T.Y., Maire, M., Belongie, S., Hays, J., Perona, P., Ramanan, D., Dollár, P., Zitnick, C.L.: Microsoft coco: Common objects in context. In: ECCV (2014)

2014

Earlier work this paper cites.

Vaswani, A., Shazeer, N., Parmar, N., Uszkoreit, J., Jones, L., Gomez, A.N., Kaiser, Ł., Polosukhin, I.: Attention is all you need. In: NeurIPS (2017)

2017

Earlier work this paper cites.

Zhang, H., Xu, T., Li, H., Zhang, S., Wang, X., Huang, X., Metaxas, D.N.: Stackgan: Text to photo-realistic image synthesis with stacked generative adversarial networks. In: ICCV (2017)

2017

Earlier work this paper cites.

Devlin, J., Chang, M.W., Lee, K., Toutanova, K.: Bert: Pre-training of deep bidirectional transformers for language understanding. In: NAACL (2019)

2019

Earlier work this paper cites.

Loshchilov, I., Hutter, F.: Decoupled weight decay regularization. In: ICLR (2019)

2019

Earlier work this paper cites.

Zhu, M., Pan, P., Chen, W., Yang, Y.: Dm-gan: Dynamic memory generative adversarial networks for text-to-image synthesis. In: CVPR (2019)

2019

Earlier work this paper cites.

Ho, J., Jain, A., Abbeel, P.: Denoising diffusion probabilistic models. In: NeurIPS (2020)

2020

Earlier work this paper cites.

Khosla, P., Teterwak, P., Wang, C., Sarna, A., Tian, Y., Isola, P., Maschinot, A., Liu, C., Krishnan, D.: Supervised contrastive learning. NeurIPS (2020)

2020

Earlier work this paper cites.

Zhang, T., Kishore, V., Wu, F., Weinberger, K.Q., Artzi, Y.: Bertscore: Evaluating text generation with bert. In: ICLR (2020)

2020

Earlier work this paper cites.

Hessel, J., Holtzman, A., Forbes, M., Bras, R.L., Choi, Y.: Clipscore: A reference-free evaluation metric for image captioning. In: EMNLP (2021)

2021

Earlier work this paper cites.

Mielke, S.J., Alyafeai, Z., Salesky, E., Raffel, C., Dey, M., Gallé, M., Raja, A., Si, C., Lee, W.Y., Sagot, B., et al.: Between words and characters: a brief history of open-vocabulary modeling and tokenization in nlp. arXiv preprint arXiv:2112.10508 (2021)

Original

2021

Earlier work this paper cites.

Radford, A., Kim, J.W., Hallacy, C., Ramesh, A., Goh, G., Agarwal, S., Sastry, G., Askell, A., Mishkin, P., Clark, J., et al.: Learning transferable visual models from natural language supervision. In: ICML (2021)

2021

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: ICML (2021)

2021

Earlier work this paper cites.

Daras, G., Dimakis, A.G.: Discovering the hidden vocabulary of dalle-2. arXiv preprint arXiv:2206.00169 (2022)

Original

2022

Earlier work this paper cites.

Dong, Q., Li, L., Dai, D., Zheng, C., Wu, Z., Chang, B., Sun, X., Xu, J., Sui, Z.: A survey on in-context learning. arXiv preprint arXiv:2301.00234 (2022)

Original

2022

Earlier work this paper cites.

Gu, S., Chen, D., Bao, J., Wen, F., Zhang, B., Chen, D., Yuan, L., Guo, B.: Vector quantized diffusion model for text-to-image synthesis. In: CVPR (2022)

2022

Earlier work this paper cites.

Millière, R.: Adversarial attacks on image generation with made-up words. arXiv preprint arXiv:2208.04135 (2022)

Original

2022

Earlier work this paper cites.

Nichol, A., Dhariwal, P., Ramesh, A., Shyam, P., Mishkin, P., McGrew, B., Sutskever, I., Chen, M.: Glide: Towards photorealistic image generation and editing with text-guided diffusion models. In: ICML (2022)

2022

Cited alongside, same era.

Ramesh, A., Dhariwal, P., Nichol, A., Chu, C., Chen, M.: Hierarchical text-conditional image generation with clip latents. arXiv preprint arXiv:2204.06125 (2022)

Original

2022

Cited alongside, same era.

Rombach, R., Blattmann, A., Lorenz, D., Esser, P., Ommer, B.: High-resolution image synthesis with latent diffusion models. In: CVPR (2022)

2022

Cited alongside, same era.

Saharia, C., Chan, W., Saxena, S., Li, L., Whang, J., Denton, E.L., Ghasemipour, K., Gontijo Lopes, R., Karagol Ayan, B., Salimans, T., et al.: Photorealistic text-to-image diffusion models with deep language understanding. In: NeurIPS (2022)

2022

Cited alongside, same era.

Yang, Y., Hui, B., Yuan, H., Gong, N., Cao, Y.: Sneakyprompt: Jailbreaking text-to-image generative models. In: IEEE Symposium on Security and Privacy (2023)

2023

Later among the works it cites.

Zheng, Y., Yeh, R.A.: Imma: Immunizing text-to-image models against malicious adaptation. arXiv preprint arXiv:2311.18815 (2023)

Original

2023

Later among the works it cites.

Zhuang, H., Zhang, Y., Liu, S.: A pilot study of query-free adversarial attack against stable diffusion. In: CVPR Workshops (2023)

2023

Later among the works it cites.

Zou, A., Wang, Z., Kolter, J.Z., Fredrikson, M.: Universal and transferable adversarial attacks on aligned language models. arXiv preprint arXiv:2307.15043 (2023)

Original

2023

Later among the works it cites.

Website: Dall-e 3 system card (2023), Link

2023