7 citations · 7 across the 6 of their papers we have counts for
5 papers · 1 filter
Multi-Turn Neural Transparency: Surfacing Neural Activations Improves User Calibration to LLM Behavioral Drift
Sheer Karny, Anthony Baez, Pat Pataranutaporn
Chatbot behavior is often opaque to users, as responses can shift unpredictably across a conversation, drifting toward sycophancy, toxicity, or other unsafe responses. This can lea…
AI-Wrapped: Participatory, Privacy-Preserving Measurement of Longitudinal LLM Use In-the-Wild
Cathy Mengying Fang, Sheer Karny, Chayapatr Archiwaranguprok +3
Alignment research on large language models (LLMs) increasingly depends on understanding how these systems are used in everyday contexts. Yet naturalistic interaction data is diffi…
Neural Transparency: Mechanistic Interpretability Interfaces for Anticipating Model Behaviors for Personalized AI
Sheer Karny, Anthony Baez, Pat Pataranutaporn
Millions of users now design personalized LLM-based chatbots that shape their daily interactions, yet they can only roughly anticipate how their design choices will manifest as beh…
Atlas of Human-AI Interaction (v1): An Interactive Meta-Science Platform for Large-Scale Research Literature Sensemaking
Chayapatr Archiwaranguprok, Awu Chen, Sheer Karny +3
Human-AI interaction researchers face an overwhelming challenge: synthesizing insights from thousands of empirical studies to understand how AI impacts people and inform effective…
"My Boyfriend is AI": A Computational Analysis of Human-AI Companionship in Reddit's AI Community
Pat Pataranutaporn, Sheer Karny, Chayapatr Archiwaranguprok +3
The emergence of AI companion applications has created novel forms of intimate human-AI relationships, yet empirical research on these communities remains limited. We present the f…