Song, Dawn

Language Models are Open Knowledge Graphs

Wang, C., Liu, X., & Song, D. (2020) · arXiv

Topic ModelingAdvanced Graph Neural Networks

Cited by 79

Imitation Attacks and Defenses for Black-box Machine Translation Systems

Wallace, E., Stern, M., & Song, D. (2020) · Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)

Adversarial Robustness in Machine LearningTopic Modeling

Cited by 75

Representation Engineering: A Top-Down Approach to AI Transparency

Zou, A., Phan, L., Chen, S., Campbell, J., Guo, P., Ren, R., Pan, A., Yin, X., Mazeika, M., Dombrowski, A.-K., et al. (2023) · arXiv

Explainable Artificial Intelligence (XAI)Ethics and Social Impacts of AI

Cited by 65

Identifying and Mitigating the Security Risks of Generative AI

Barrett, C., Boyd, B., Bursztein, E., Carlini, N., Chen, B., Choi, J., Chowdhury, A. R., Christodorescu, M., Datta, A., Feizi, S., et al. (2023) · Foundations and Trends® in Privacy and Security

Adversarial Robustness in Machine LearningInformation and Cyber Security

Cited by 57

The False Promise of Imitating Proprietary LLMs

Gudibande, A., Wallace, E., Snell, C., Geng, X., Liu, H., Abbeel, P., Levine, S., & Song, D. (2023) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 48

LLM-PBE: Assessing Data Privacy in Large Language Models

Li, Q., Hong, J., Xie, C., Tan, J., Xin, R., Hou, J., Yin, X., Wang, Z., Hendrycks, D., Wang, Z., et al. (2024) · Proceedings of the VLDB Endowment

Privacy-Preserving Technologies in DataAdversarial Robustness in Machine Learning

Cited by 42

LLM-PBE: Assessing Data Privacy in Large Language Models

Li, Q., Hong, J., Xie, C., Tan, J., Xin, R., Hou, J., Yin, X., Wang, Z., Hendrycks, D., Wang, Z., et al. (2024) · arXiv

Privacy-Preserving Technologies in DataAdversarial Robustness in Machine Learning

Cited by 42

Synthetic Datasets for Neural Program Synthesis

Shin, R., Kant, N., Gupta, K., Bender, C., Trabucco, B., Singh, R., & Song, D. (2019) · arXiv

Evolutionary Algorithms and ApplicationsTeaching and Learning Programming

Cited by 25

Hidden Persuaders: LLMs’ Political Leaning and Their Influence on Voters

Potter, Y., Lai, S., Kim, J., Evans, J., & Song, D. (2024) · Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing

Ethics and Social Impacts of AISocial Media and Politics

Cited by 21

Synthesize, Execute and Debug: Learning to Repair for Neural Program Synthesis

Gupta, K., Christensen, P. E., Chen, X., & Song, D. (2020) · arXiv

Teaching and Learning ProgrammingEvolutionary Algorithms and Applications

Cited by 18

Progent: Securing AI Agents with Privilege Control

Shi, T., He, J., Wang, Z., Li, H., Wu, L., Guo, W., & Song, D. (2025) · arXiv

Security and Verification in ComputingAdversarial Robustness in Machine Learning

Cited by 3

Latent Execution for Neural Program Synthesis

Chen, X., Song, D., & Tian, Y. (2021) · arXiv

Software Engineering ResearchTeaching and Learning Programming

Cited by 2

Scaling Agent Learning via Experience Synthesis

Chen, Z., Zhao, Z., Zhang, K., Liu, B., Qi, Q., Wu, Y., Kalluri, T., Cao, S., Xiong, Y., Tong, H., et al. (2025) · arXiv

Reinforcement Learning in RoboticsDomain Adaptation and Few-Shot Learning

Cited by 0

An Illusion of Progress? Assessing the Current State of Web Agents

Xue, T., Qi, W., Shi, T., Song, C. H., Gou, B., Song, D., Sun, H., & Su, Y. (2025) · arXiv

Web Data Mining and AnalysisInformation Retrieval and Search Behavior

Cited by 0

In-context watermarks for large language models

Liu, Y., Zhao, X., Kruegel, C., Song, D., & Bu, Y. (2025) · arXiv

Advanced Steganography and Watermarking TechniquesAdversarial Robustness in Machine Learning

Cited by 0