1 citations · 1 across the 3 of their papers we have counts for
6 papers
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
LLMs are increasingly used for personal advice on relationships, work, moral dilemmas, and crises. Post-training selects a stable, prosocial Assistant persona, but good advice requ…
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…
When AI Gives Advice: Evaluating AI and Human Responses to Online Advice-Seeking for Well-Being
Harsh Kumar, Jasmine Chahal, Yinuo Zhao +4
Seeking advice is a core human behavior that the internet has reinvented twice: first through forums and Q&A communities that crowdsource public guidance, and now through large lan…
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…
Human Creativity in the Age of LLMs: Randomized Experiments on Divergent and Convergent Thinking
Harsh Kumar, Jonathan Vincentius, Ewan Jordan +1
Large language models are transforming the creative process by offering unprecedented capabilities to algorithmically generate ideas. While these tools can enhance human creativity…