Safe-CLIP: Removing NSFW Concepts from Vision-and-Language Models

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.

Cao, Y., Yang, J.: Towards Making Systems Forget with Machine Unlearning. In: IEEE Symposium on Security and Privacy (2015)

2015

Earlier work this paper cites.

Karpathy, A., Fei-Fei, L.: Deep visual-semantic alignments for generating image descriptions. In: CVPR (2015)

2015

Earlier work this paper cites.

Kingma, D.P., Ba, J.: Adam: A Method for Stochastic Optimization. In: ICLR (2015)

2015

Earlier work this paper cites.

Kembhavi, A., Salvato, M., Kolve, E., Seo, M., Hajishirzi, H., Farhadi, A.: A Diagram is Worth a Dozen Images. In: ECCV (2016)

2016

Earlier work this paper cites.

Christiano, P.F., Leike, J., Brown, T., Martic, M., Legg, S., Amodei, D.: Deep reinforcement learning from human preferences. In: NeurIPS (2017)

2017

Earlier work this paper cites.

Crone, D.L., Bode, S., Murawski, C., Laham, S.M.: The Socio-Moral Image Database (SMID): A novel stimulus set for the study of social, moral and affective processes. PloS one 13

2018

Earlier work this paper cites.

Oord, A.v.d., Li, Y., Vinyals, O.: Representation Learning with Contrastive Predictive Coding. arXiv preprint arXiv:1807.03748 (2018)

Original

2018

Earlier work this paper cites.

Bedapudi, P.: NudeNet: Neural Nets for Nudity Classification, Detection, and Selective Censoring (2019)

2019

Earlier work this paper cites.

Ginart, A., Guan, M., Valiant, G., Zou, J.Y.: Making AI Forget You: Data Deletion in Machine Learning. In: NeurIPS (2019)

2019

Earlier work this paper cites.

Hidayatullah, A.F., Hakim, A.M., Sembada, A.A.: Adult Content Classification on Indonesian Tweets using LSTM Neural Network. In: ICACSIS (2019)

2019

Earlier work this paper cites.

Radford, A., Wu, J., Child, R., Luan, D., Amodei, D., Sutskever, I.: Language Models are Unsupervised Multitask Learners. OpenAI Blog 1

2019

Earlier work this paper cites.

Sanh, V., Debut, L., Chaumond, J., Wolf, T.: DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lighter. arXiv preprint arXiv:1910.01108 (2019)

Original

2019

Earlier work this paper cites.

Gandhi, S., Kokkula, S., Chaudhuri, A., Magnani, A., Stanley, T., Ahmadi, B., Kandaswamy, V., Ovenc, O., Mannor, S.: Scalable Detection of Offensive and Non-compliant Content/Logo in Product Images. In: WACV (2020)

2020

Earlier work this paper cites.

Golatkar, A., Achille, A., Soatto, S.: Eternal Sunshine of the Spotless Net: Selective Forgetting in Deep Networks. In: CVPR (2020)

2020

Earlier work this paper cites.

Birhane, A., Prabhu, V.U.: Large image datasets: A pyrrhic win for computer vision? In: WACV (2021)

2021

Earlier work this paper cites.

Birhane, A., Prabhu, V.U., Kahembwe, E.: Multimodal datasets: misogyny, pornography, and malignant stereotypes. arXiv preprint arXiv:2110.01963 (2021)

Original

2021

Earlier work this paper cites.

Hu, E.J., Shen, Y., Wallis, P., Allen-Zhu, Z., Li, Y., Wang, S., Wang, L., Chen, W.: LoRA: Low-Rank Adaptation of Large Language Models. arXiv preprint arXiv:2106.09685 (2021)

Original

2021

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. arXiv preprint arXiv:2112.10741 (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., Krueger, G., Sutskever, I.: Learning Transferable Visual Models From Natural Language Supervision. In: ICML (2021)

2021

Earlier work this paper cites.

Schuhmann, C., Vencu, R., Beaumont, R., Kaczmarczyk, R., Mullis, C., Katta, A., Coombes, T., Jitsev, J., Komatsuzaki, A.: LAION-400M: Open Dataset of CLIP-Filtered 400 Million Image-Text Pairs. In: NeurIPS Workshops (2021)

2021

Cited alongside, same era.

Wang, M., Xing, J., Liu, Y.: ActionCLIP: A New Paradigm for Video Action Recognition. arXiv preprint arXiv:2109.08472 (2021)

Original

2021

Cited alongside, same era.

Bakker, M., Chadwick, M., Sheahan, H., Tessler, M., Campbell-Gillingham, L., Balaguer, J., McAleese, N., Glaese, A., Aslanides, J., Botvinick, M., et al.: Fine-tuning language models to find agreement among humans with diverse preferences. In: NeurIPS (2022)

2022

Cited alongside, same era.

Cauteruccio, F., Corradini, E., Terracina, G., Ursino, D., Virgili, L.: Extraction and analysis of text patterns from nsfw adult content in reddit. Data & Knowledge Engineering 138

2022

Cited alongside, same era.

Liu, H., Li, C., Li, Y., Lee, Y.J.: Improved Baselines with Visual Instruction Tuning. arXiv preprint arXiv:2310.03744 (2023)

Original

2023

Closest in time.

Liu, H., Li, C., Wu, Q., Lee, Y.J.: Visual Instruction Tuning. In: NeurIPS (2023)

2023

Closest in time.

Liu, Y., Singh, A., Freeman, C.D., Co-Reyes, J.D., Liu, P.J.: Improving Large Language Model Fine-tuning for Solving Math Problems. arXiv preprint arXiv:2310.10047 (2023)

Original

2023

Closest in time.

Markov, T., Zhang, C., Agarwal, S., Nekoul, F.E., Lee, T., Adler, S., Jiang, A., Weng, L.: A Holistic Approach to Undesired Content Detection in the Real World. In: AAAI (2023)

2023

Closest in time.

Rafailov, R., Sharma, A., Mitchell, E., Ermon, S., Manning, C.D., Finn, C.: Direct Preference Optimization: Your Language Model is Secretly a Reward Model. In: NeurIPS (2023)