15 papers
DISARM-ing the Hidden Puppetmaster: An Interface for Exposing Manipulative Tactics in Large Language Models
Kynnedy Simone Smith, Kantwon Rogers, Priyal Shrivastava +3
Large language models (LLMs) can covertly steer users' beliefs through emotionally manipulative tactics, yet little is known about how interfaces can protect users as such influenc…
Exploring the Interaction of Explanation Styles, Context, and Trust of AI Privacy Redaction in AI-mediated Interactions
Roshni Kaushik, Maarten Sap, Koichi Onoue
AI-mediated communication is increasingly being utilized to help facilitate interactions; however, in privacy sensitive domains, an AI mediator has the additional challenge of cons…
CCBENCH: Assessing LLM Cultural Competence via Implicitly Signaled Norms using Health Queries
Vasudha Varadarajan, Akhila Yerukola, Mona T. Diab +1
To interact with users fairly and without stereotyping, AI models must display cultural competency, i.e., the ability to infer and adapt to a user's implicitly signaled cultural va…
Lost in Delusion: Examining LLM Safety Under User Delusions and Distress
Andrew Aquilina, Chetna Nihalani, Vasudha Varadarajan +3
LLM chatbots increasingly serve as a first source of support for people in psychological distress, including those whose distress is entangled with delusional beliefs. Prior work o…
Public Perceptions and Acceptance of Socially Intelligent AI Agents
Leena Mathur, Jenny T. Liang, Vasudha Varadarajan +6
AI researchers have been advancing socially intelligent AI agents (Social-AI) across embodiments, from chatbots to physical robots. As Social-AI agents move from labs into everyday…
Framing an AI with Values Reduces AI Reliance in AI-supported Writing Tasks
Alice Gao, Andrew N. Meltzoff, Maarten Sap +1
Despite a global user base adopting large language models (LLMs) for daily writing tasks, model suggestions tend to align with Western values. Research has shown users commonly acc…
Reinforcing Human Behavior Simulation via Verbal Feedback
Weiwei Sun, Xuhui Zhou, Jiarui Liu +13
Humans learn social norms and behaviors from verbal feedback (e.g., a parent saying "that was rude" or a friend explaining "here's why that hurt"). Yet, learning from feedback for…
SOTOPIA-TOM: Evaluating Privacy and Information Management in Multi-Agent Interaction with Theory of Mind
Yashwanth YS, Ruichen Wang, Shihua Zeng +4
As LLM-based agents are increasingly interacting in multi-party settings, they need to properly handle information asymmetry, i.e., knowing when and to whom to disclose information…
Imperfectly Cooperative Human-AI Interactions: Comparing the Impacts of Human and AI Attributes in Simulated and User Studies
Myke C. Cohen, Mingqian Zheng, Neel Bhandari +6
AI design characteristics and human personality traits each impact the quality and outcomes of human-AI interactions. However, their relative and joint impacts are underexplored in…
"I Just Don't Want My Work Being Fed Into The AI Blender": Queer Artists on Refusing and Resisting Generative AI
Jordan Taylor, Joel Mire, Alicia DeVrio +3
Art-making is a collective social activity through which queer people engage in political resistance, develop identities, archive queer memory, and form community. However, in rece…
Examining the Effect of Explanations of AI Privacy Redaction in AI-mediated Interactions
Roshni Kaushik, Maarten Sap, Koichi Onoue
AI-mediated communication is increasingly being utilized to help facilitate interactions; however, in privacy sensitive domains, an AI mediator has the additional challenge of cons…
The Hidden Puppet Master: Predicting Human Belief Change in Manipulative LLM Dialogues
Jocelyn Shen, Amina Luvsanchultem, Jessica Kim +6
As users increasingly turn to LLMs for practical and personal advice, they become vulnerable to subtle steering toward hidden incentives misaligned with their own interests. While…
Mind the Sim2Real Gap in User Simulation for Agentic Tasks
Xuhui Zhou, Weiwei Sun, Qianou Ma +8
As NLP evaluation shifts from static benchmarks to multi-turn interactive settings, LLM-based simulators have become widely used as user proxies, serving two roles: generating user…
Martingale Score: An Unsupervised Metric for Bayesian Rationality in LLM Reasoning
Zhonghao He, Tianyi Qiu, Hirokazu Shirado +1
Recent advances in reasoning techniques have substantially improved the performance of large language models (LLMs), raising expectations for their ability to provide accurate, tru…
Critical or Compliant? The Double-Edged Sword of Reasoning in Chain-of-Thought Explanations
Eunkyu Park, Wesley Hanwen Deng, Vasudha Varadarajan +4
Explanations are often promoted as tools for transparency, but they can also foster confirmation bias; users may assume reasoning is correct whenever outputs appear acceptable. We…