44 citations · 46 across the 6 of their papers we have counts for
5 papers · 1 filter
Social Priors: Descriptions of AI Users Shape How Language Models Trust and Cooperate
Harsh Kumar, George Eilender, Ashton Anderson
Descriptions of how people use AI are becoming training data for the next generation of models. We ask whether what a model reads about its users changes how it treats people. Usin…
Position: We Need Large Language Models Optimized For Our Well-Being
Ashton Anderson, Harsh Kumar, Louis Tay +1
Large language models are useful because we taught them to give us what we want. This works when success can be judged immediately, but people increasingly bring these systems thei…
Diagnosing and Repairing Persona Collapse in LLM Advice
Harsh Kumar, Karina Vold, Louis Tay +1
A good advisor comforts someone in crisis, challenges someone in denial, and gives practical guidance on a logistical question. We ask whether large language models (LLMs) vary the…
Human Thinking under Plural LLM Assistance: Mathematical Problem Solving and Open-Ended Writing
Harsh Kumar, Jace Mu, Jonathan Vincentius +1
Large language models are changing not only the kind of assistance people receive, but also how that assistance is organized. Instead of working with a single general-purpose chatb…
Transforming GenAI Policy to Prompting Instruction: An RCT of Scalable Prompting Interventions in a CS1 Course
Ruiwei Xiao, Runlong Ye, Xinying Hou +4
Despite universal GenAI adoption, students cannot distinguish task performance from actual learning and lack skills to leverage AI for learning, leading to worse exam performance w…