Sap, Maarten

Can LLMs Keep a Secret? Testing Privacy Implications of Language Models via Contextual Integrity Theory

Mireshghallah, N., Kim, H., Zhou, X., Tsvetkov, Y., Sap, M., Shokri, R., & Choi, Y. (2023) · arXiv

Privacy-Preserving Technologies in DataPrivacy, Security, and Data Protection

Cited by 14

Agents of Chaos

Shapira, N., Wendler, C., Yen, A., Sarti, G., Pal, K., Floody, O., Belfki, A., Loftus, A., Jannali, A. R., Prakash, N., et al. (2026) · arXiv

Adversarial Robustness in Machine LearningEthics and Social Impacts of AI

Cited by 6

SODA: Million-scale Dialogue Distillation with Social Commonsense Contextualization

Kim, H., Hessel, J., Jiang, L., West, P., Lu, X., Yu, Y., Zhou, P., Bras, R. L., Alikhani, M., Kim, G., et al. (2022) · arXiv

Speech and dialogue systemsTopic Modeling

Cited by 3

On the Resilience of LLM-Based Multi-Agent Collaboration with Faulty Agents

Huang, J.-T., Zhou, J., Jin, T., Zhou, X., Chen, Z., Wang, W., Yuan, Y., Lyu, M. R., & Sap, M. (2024) · arXiv

Multi-Agent Systems and NegotiationNatural Language Processing Techniques

Cited by 1

Ambig-SWE: Interactive Agents to Overcome Underspecificity in Software Engineering

Vijayvargiya, S., Zhou, X., Yerukola, A., Sap, M., & Neubig, G. (2025) · arXiv

Software Engineering ResearchSoftware Engineering Techniques and Practices

Cited by 0

OpenAgentSafety: A Comprehensive Framework for Evaluating Real-World AI Agent Safety

Vijayvargiya, S., Soni, A. B., Zhou, X., Wang, Z. Z., Dziri, N., Neubig, G., & Sap, M. (2025) · arXiv

Adversarial Robustness in Machine LearningEthics and Social Impacts of AI

Cited by 0