Song, Dawn

Advances and Open Problems in Federated Learning

Kairouz, P., McMahan, H. B., Avent, B., Bellet, A., Bennis, M., Bhagoji, A. N., Bonawitz, K., Charles, Z., Cormode, G., Cummings, R., et al. (2019) · arXiv

Privacy-Preserving Technologies in DataStochastic Gradient Optimization Techniques

Cited by 7,857

Robust physical-world attacks on deep learning visual classification

Eykholt, K., Evtimov, I., Fernandes, E., Li, B., Rahmati, A., Xiao, C., Prakash, A., Kohno, T., & Song, D. (2018) · 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition

Adversarial Robustness in Machine LearningDigital Media Forensic Detection

Cited by 2,173

Delving into Transferable Adversarial Examples and Black-box Attacks

Liu, Y., Chen, X., Liu, C., & Song, D. (2016) · arXiv

Adversarial Robustness in Machine LearningDigital Media Forensic Detection

Cited by 1,310

The Many Faces of Robustness: A Critical Analysis of Out-of-Distribution Generalization

Hendrycks, D., Basart, S., Mu, N., Kadavath, S., Wang, F., Dorundo, E., Desai, R., Zhu, T., Parajuli, S., Guo, M., et al. (2021) · 2021 IEEE/CVF International Conference on Computer Vision (ICCV)

Domain Adaptation and Few-Shot LearningAdversarial Robustness in Machine Learning

Cited by 1,250

Natural Adversarial Examples

Hendrycks, D., Zhao, K., Basart, S., Steinhardt, J., & Song, D. (2021) · 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Adversarial Robustness in Machine LearningMachine Learning and Data Classification

Cited by 1,090

Natural Adversarial Examples

Hendrycks, D., Zhao, K., Basart, S., Steinhardt, J., & Song, D. (2019) · arXiv

Adversarial Robustness in Machine LearningMachine Learning and Data Classification

Cited by 1,058

Targeted Backdoor Attacks on Deep Learning Systems Using Data Poisoning

Chen, X., Liu, C., Li, B., Lu, K., & Song, D. (2017) · arXiv

Adversarial Robustness in Machine LearningDigital Media Forensic Detection

Cited by 1,039

Extracting Training Data from Large Language Models

Carlini, N., Tramer, F., Wallace, E., Jagielski, M., Herbert-Voss, A., Lee, K., Roberts, A., Brown, T., Song, D., Erlingsson, U., et al. (2020) · arXiv

Adversarial Robustness in Machine LearningPrivacy-Preserving Technologies in Data

Cited by 727

Using Self-Supervised Learning Can Improve Model Robustness and Uncertainty

Hendrycks, D., Mazeika, M., Kadavath, S., & Song, D. (2019) · arXiv

Adversarial Robustness in Machine LearningDomain Adaptation and Few-Shot Learning

Cited by 634

The Secret Sharer: Evaluating and Testing Unintended Memorization in Neural Networks

Carlini, N., Liu, C., Erlingsson, Ú., Kos, J., & Song, D. (2018) · arXiv

Privacy-Preserving Technologies in DataAdversarial Robustness in Machine Learning

Cited by 629

Aligning AI With Shared Human Values

Hendrycks, D., Burns, C., Basart, S., Critch, A., Li, J., Song, D., & Steinhardt, J. (2020) · arXiv

Ethics and Social Impacts of AIPsychology of Moral and Emotional Judgment

Cited by 517

The Secret Revealer: Generative Model-Inversion Attacks Against Deep Neural Networks

Zhang, Y., Jia, R., Pei, H., Wang, W., Li, B., & Song, D. (2019) · arXiv

Privacy-Preserving Technologies in DataAdversarial Robustness in Machine Learning

Cited by 465

Suspended accounts in retrospect: an analysis of twitter spam

Thomas, K., Grier, C., Song, D., & Paxson, V. (2011) · Proceedings of the 2011 ACM SIGCOMM conference on Internet measurement conference

Spam and Phishing DetectionCybercrime and Law Enforcement Studies

Cited by 439

Dataset Security for Machine Learning: Data Poisoning, Backdoor Attacks, and Defenses

Goldblum, M., Tsipras, D., Xie, C., Chen, X., Schwarzschild, A., Song, D., Madry, A., Li, B., & Goldstein, T. (2023) · IEEE Transactions on Pattern Analysis and Machine Intelligence

Adversarial Robustness in Machine LearningPrivacy-Preserving Technologies in Data

Cited by 362

Managing extreme AI risks amid rapid progress

Bengio, Y., Hinton, G., Yao, A., Song, D., Abbeel, P., Darrell, T., Harari, Y. N., Zhang, Y.-Q., Xue, L., Shalev-Shwartz, S., et al. (2024) · Science

Ethics and Social Impacts of AIDigitalization, Law, and Regulation

Cited by 349

Measuring Mathematical Problem Solving With the MATH Dataset

Hendrycks, D., Burns, C., Kadavath, S., Arora, A., Basart, S., Tang, E., Song, D., & Steinhardt, J. (2021) · arXiv

Topic ModelingMathematics, Computing, and Information Processing

Cited by 306

Measuring Massive Multitask Language Understanding

Hendrycks, D., Burns, C., Basart, S., Zou, A., Mazeika, M., Song, D., & Steinhardt, J. (2020) · arXiv

Topic ModelingMultimodal Machine Learning Applications

Cited by 291

On the Feasibility of Internet-Scale Author Identification

Narayanan, A., Paskov, H., Gong, N. Z., Bethencourt, J., Stefanov, E., Shin, E. C. R., & Song, D. (2012) · 2012 IEEE Symposium on Security and Privacy

Authorship Attribution and ProfilingUser Authentication and Security Systems

Cited by 261

A Berkeley View of Systems Challenges for AI

Stoica, I., Song, D., Popa, R. A., Patterson, D., Mahoney, M. W., Katz, R., Joseph, A. D., Jordan, M., Hellerstein, J. M., Gonzalez, J. E., et al. (2017) · arXiv

Artificial Intelligence ApplicationsAdvanced Neural Network Applications

Cited by 171

Tree-to-tree neural networks for program translation

Chen, X., Liu, C., & Song, D. (2018) · arXiv

Software Engineering ResearchNatural Language Processing Techniques

Cited by 157

Measuring Coding Challenge Competence With APPS

Hendrycks, D., Basart, S., Kadavath, S., Mazeika, M., Arora, A., Guo, E., Burns, C., Puranik, S., He, H., Song, D., et al. (2021) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 142

Delving into adversarial attacks on deep policies

Kos, J., & Song, D. (2017) · arXiv

Adversarial Robustness in Machine LearningSecurity and Verification in Computing

Cited by 135

Assessing Generalization in Deep Reinforcement Learning

Packer, C., Gao, K., Kos, J., Krähenbühl, P., Koltun, V., & Song, D. (2018) · arXiv

Reinforcement Learning in RoboticsDomain Adaptation and Few-Shot Learning

Cited by 114

Optimal Lower Bound for Differentially Private Multi-party Aggregation

Chan, T.-H. H., Shi, E., & Song, D. (2012) · Lecture Notes in Computer Science

Privacy-Preserving Technologies in DataCryptography and Data Security

Cited by 82