Anderson, Hyrum

The Malicious Use of Artificial Intelligence: Forecasting, Prevention, and Mitigation

Brundage, M., Avin, S., Clark, J., Toner, H., Eckersley, P., Garfinkel, B., Dafoe, A., Scharre, P., Zeitzoff, T., Filar, B., et al. (2018) · arXiv

Adversarial Robustness in Machine LearningEthics and Social Impacts of AI

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The Malicious Use of Artificial Intelligence: Forecasting, Prevention, and Mitigation

Brundage, M., Avin, S., Clark, J., Toner, H., Eckersley, P., Garfinkel, B., Dafoe, A., Scharre, P., Zeitzoff, T., Filar, B., et al. (2018) · Apollo - University of Cambridge Repository

Adversarial Robustness in Machine LearningEthics and Social Impacts of AI

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Tree of Attacks: Jailbreaking Black-Box LLMs Automatically

Mehrotra, A., Zampetakis, M., Kassianik, P., Nelson, B., Anderson, H., Singer, Y., & Karbasi, A. (2023) · arXiv

Adversarial Robustness in Machine LearningSecurity and Verification in Computing

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Poisoning Web-Scale Training Datasets is Practical

Carlini, N., Jagielski, M., Choquette-Choo, C. A., Paleka, D., Pearce, W., Anderson, H., Terzis, A., Thomas, K., & Tramèr, F. (2024) · 2024 IEEE Symposium on Security and Privacy (SP)

Adversarial Robustness in Machine LearningPrivacy-Preserving Technologies in Data

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Poisoning Web-Scale Training Datasets is Practical

Carlini, N., Jagielski, M., Choquette-Choo, C. A., Paleka, D., Pearce, W., Anderson, H., Terzis, A., Thomas, K., & Tramèr, F. (2023) · arXiv

Adversarial Robustness in Machine LearningPrivacy-Preserving Technologies in Data

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