44 citations · 58 across the 9 of their papers we have counts for
5 papers · 1 filter
Behavior Latticing: Inferring User Motivations from Unstructured Interactions
Dora Zhao, Michelle S. Lam, Diyi Yang +1
A long-standing vision of computing is the personal AI system: one that understands us well enough to address our underlying needs. Today's AI focuses on what users do, ignoring wh…
Just-In-Time Objectives: A General Approach for Specialized AI Interactions
Michelle S. Lam, Omar Shaikh, Hallie Xu +5
Large language models promise a broad set of functions, but when not given a specific objective, they default to generic results. We demonstrate that inferring the user's in-the-mo…
Knoll: Creating a Knowledge Ecosystem for Large Language Models
Dora Zhao, Diyi Yang, Michael S. Bernstein
Large language models are designed to encode general purpose knowledge about the world from Internet data. Yet, a wealth of information falls outside this scope -- ranging from per…
Creating General User Models from Computer Use
Omar Shaikh, Shardul Sapkota, Shan Rizvi +4
Human-computer interaction has long imagined technology that understands us-from our preferences and habits, to the timing and purpose of our everyday actions. Yet current user mod…
Rehearsal: Simulating Conflict to Teach Conflict Resolution
Omar Shaikh, Valentino Chai, Michele J. Gelfand +2
Interpersonal conflict is an uncomfortable but unavoidable fact of life. Navigating conflict successfully is a skill -- one that can be learned through deliberate practice -- but f…