Phuong, Mary

Gemini: A Family of Highly Capable Multimodal Models

Gemini Team, Anil, R., Borgeaud, S., Alayrac, J.-B., Yu, J., Soricut, R., Schalkwyk, J., Dai, A. M., Hauth, A., Millican, K., et al. (2023) · arXiv

Multimodal Machine Learning ApplicationsTopic Modeling

Cited by 990

Model evaluation for extreme risks

Shevlane, T., Farquhar, S., Garfinkel, B., Phuong, M., Whittlestone, J., Leung, J., Kokotajlo, D., Marchal, N., Anderljung, M., Kolt, N., et al. (2023) · arXiv

Ethics and Social Impacts of AIAdversarial Robustness in Machine Learning

Cited by 66

Goal Misgeneralization: Why Correct Specifications Aren't Enough For Correct Goals

Shah, R., Varma, V., Kumar, R., Phuong, M., Krakovna, V., Uesato, J., & Kenton, Z. (2022) · arXiv

Ethics and Social Impacts of AIAdversarial Robustness in Machine Learning

Cited by 16

Evaluating Frontier Models for Dangerous Capabilities

Phuong, M., Aitchison, M., Catt, E., Cogan, S., Kaskasoli, A., Krakovna, V., Lindner, D., Rahtz, M., Assael, Y., Hodkinson, S., et al. (2024) · arXiv

Ethics and Social Impacts of AIAdversarial Robustness in Machine Learning

Cited by 11

Evaluating Frontier Models for Stealth and Situational Awareness

Phuong, M., Zimmermann, R. S., Wang, Z., Lindner, D., Krakovna, V., Cogan, S., Dafoe, A., Ho, L., & Shah, R. (2025) · arXiv

Ethics and Social Impacts of AIAdversarial Robustness in Machine Learning

Cited by 1