15 papers
Can LLM Code Explanations Adapt to Diverse Problem-Solvers' Needs?
Andrew Anderson, David Piorkowski, Justin Weisz +2
Large language model (LLM) code explanations can support people in solving code-related problems, yet prior work has shown that people have diverse problem-solving styles. If expla…
Next-Billion AI Index: The compass for AI utility and adoption in the global majority
Ambrish Rawat, Jessica He, Subhabrata Majumdar +6
Generative AI assessments remain dominated by frontier capability benchmarks that often fail to capture whether systems can be sustainably deployed, adapted, and trusted in locally…
A Task-Driven Human-AI Collaboration: When to Automate, When to Collaborate, When to Challenge
Saleh Afroogh, Kush R. Varshney, Jason D'Cruz
According to several empirical investigations, despite enhancing human capabilities, human-AI cooperation frequently falls short of expectations and fails to reach true synergy. We…
An Algebraic Exposition of the Theory of Dyadic Morality
Kush R. Varshney
This paper provides an algebraic exposition of the theory of dyadic morality (TDM), a psychological model of moral judgment grounded in a simple two-node template: an intentional a…
AI Steerability 360: A Toolkit for Steering Large Language Models
Erik Miehling, Karthikeyan Natesan Ramamurthy, Praveen Venkateswaran +10
The AI Steerability 360 toolkit is an extensible, open-source Python library for steering LLMs. Steering abstractions are designed around four model control surfaces: input (modifi…
Story Arena: A Multi-Agent Environment for Envisioning the Future of Software Engineering
Justin D. Weisz, Michael Muller, Kush R. Varshney
What better way to understand the impact of AI on software engineering than to ask AI itself? We constructed Story Arena, a multi-agent "writer's room" in which multiple AI agents,…