1 citations · 1 across the 4 of their papers we have counts for
21 papers
fog: Expressing Motion and Emotion through Function Composition of AI-Generated Code
Vivian Liu, Lydia Chilton
Motion and emotion are core parts of intelligent, expressive behavior. In this paper, we introduce fog, a function composition framework for implementing and compose motion functio…
PERSONAJUDGE: Simulating Individual Human Preference Judgments with Evaluator-Specific Demonstration Data
Zeyu He, Xuan Qi, Subramanian Chidambaram +4
Large language models increasingly serve as judges in AI evaluation, but current approaches rely on consensus preferences that ignore individual evaluator variation. We propose a n…
AgentDynEx: Nudging the Mechanics and Dynamics of Multi-Agent Simulations
Jenny Ma, Riya Sahni, Karthik Sreedhar +1
Multi-agent large language model simulations have the potential to model complex human behaviors and interactions. If the mechanics are set up properly, unanticipated and valuable…
JumpStarter: Human-AI Planning with Task-Structured Context Curation
Xuanming Zhang, Sitong Wang, Jenny Ma +3
Human-AI collaboration on complex planning goals is bottlenecked by how LLM interfaces handle context: users must manually curate and re-surface relevant information across long an…
Designing for the Moment: How One-Minute Interventions Fit or Falter Across Domains
Zahra Hassanzadeh, Anne Hsu, Rachel Kornfield +8
This paper explores the design space for one-minute digital interventions that prompt immediate action without onboarding or sensing. By embracing Fogg's Behavior Model and four de…
OPeRA: A Dataset of Observation, Persona, Rationale, and Action for Evaluating LLMs on Human Online Shopping Behavior Simulation
Ziyi Wang, Yuxuan Lu, Wenbo Li +13
Can large language models (LLMs) accurately simulate the next web action of a specific user? While LLMs have shown promising capabilities in generating ``believable'' human behavio…