Ott, Myle

Unsupervised Cross-lingual Representation Learning at Scale

Conneau, A., Khandelwal, K., Goyal, N., Chaudhary, V., Wenzek, G., Guzmán, F., Grave, E., Ott, M., Zettlemoyer, L., & Stoyanov, V. (2020) · Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics

Topic ModelingNatural Language Processing Techniques

Cited by 5,637

Biological structure and function emerge from scaling unsupervised learning to 250 million protein sequences

Rives, A., Meier, J., Sercu, T., Goyal, S., Lin, Z., Liu, J., Guo, D., Ott, M., Zitnick, C. L., Ma, J., et al. (2021) · Proceedings of the National Academy of Sciences

Machine Learning in BioinformaticsProtein Structure and Dynamics

Cited by 3,286

Biological structure and function emerge from scaling unsupervised learning to 250 million protein sequences

Rives, A., Meier, J., Sercu, T., Goyal, S., Lin, Z., Liu, J., Guo, D., Ott, M., Zitnick, C. L., Ma, J., et al. (2019) · Proceedings of the National Academy of Sciences

Machine Learning in BioinformaticsProtein Structure and Dynamics

Cited by 3,280

Finding Deceptive Opinion Spam by Any Stretch of the Imagination

Ott, M., Choi, Y., Cardie, C., & Hancock, J. T. (2011) · arXiv

Spam and Phishing DetectionMisinformation and Its Impacts

Cited by 1,008

Recipes for building an open-domain chatbot

Roller, S., Dinan, E., Goyal, N., Ju, D., Williamson, M., Liu, Y., Xu, J., Ott, M., Shuster, K., Smith, E. M., et al. (2020) · arXiv

Speech and dialogue systemsTopic Modeling

Cited by 784

Recipes for Building an Open-Domain Chatbot

Roller, S., Dinan, E., Goyal, N., Ju, D., Williamson, M., Liu, Y., Xu, J., Ott, M., Smith, E. M., Boureau, Y.-L., et al. (2021) · Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume

Speech and dialogue systemsTopic Modeling

Cited by 784

Sustainable AI: Environmental Implications, Challenges and Opportunities

Wu, C.-J., Raghavendra, R., Gupta, U., Acun, B., Ardalani, N., Maeng, K., Chang, G., Behram, F. A., Huang, J., Bai, C., et al. (2021) · arXiv

Green IT and SustainabilityEnergy Efficiency in Computing

Cited by 405

PyTorch FSDP: Experiences on Scaling Fully Sharded Data Parallel

Zhao, Y., Gu, A., Varma, R., Luo, L., Huang, C.-C., Xu, M., Wright, L., Shojanazeri, H., Ott, M., Shleifer, S., et al. (2023) · arXiv

Parallel Computing and Optimization TechniquesCloud Computing and Resource Management

Cited by 227

Efficient Large Scale Language Modeling with Mixtures of Experts

Artetxe, M., Bhosale, S., Goyal, N., Mihaylov, T., Ott, M., Shleifer, S., Lin, X. V., Du, J., Iyer, S., Pasunuru, R., et al. (2021) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 223

Analyzing Uncertainty in Neural Machine Translation

Ott, M., Auli, M., Grangier, D., & Ranzato, M. (2018) · arXiv

Natural Language Processing TechniquesTopic Modeling

Cited by 140

Real or Fake? Learning to Discriminate Machine from Human Generated Text

Bakhtin, A., Gross, S., Ott, M., Deng, Y., Ranzato, M., & Szlam, A. (2019) · arXiv

Topic ModelingAuthorship Attribution and Profiling

Cited by 77

Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilities

Comanici, G., Bieber, E., Schaekermann, M., Pasupat, I., Sachdeva, N., Dhillon, I., Blistein, M., Ram, O., Zhang, D., Rosen, E., et al. (2025) · arXiv

Multimodal Machine Learning ApplicationsTopic Modeling

Cited by 69

NormFormer: Improved Transformer Pretraining with Extra Normalization

Shleifer, S., Weston, J., & Ott, M. (2021) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 24