6 papers
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…
Conversational Customization of Productivity Systems: A Design Probe of Malleable AI Interfaces
Karthik Sreedhar, Aryan Kaul, Lydia B. Chilton
Customization has long been a central goal in interactive systems, yet prior work shows that end-user tailoring occurs infrequently and is often confined to initial setup or moment…
Simulating Cooperative Prosocial Behavior with Multi-Agent LLMs: Evidence and Mechanisms for AI Agents to Inform Policy Decisions
Karthik Sreedhar, Alice Cai, Jenny Ma +2
Human prosocial cooperation is essential for our collective health, education, and welfare. However, designing social systems to maintain or incentivize prosocial behavior is chall…
DynEx: Dynamic Code Synthesis with Structured Design Exploration for Accelerated Exploratory Programming
Jenny Ma, Karthik Sreedhar, Vivian Liu +4
Recent advancements in large language models have significantly expedited the process of generating front-end code. This allows users to rapidly prototype user interfaces and ideat…
DIDUP: Dynamic Iterative Development for UI Prototyping
Jenny Ma, Karthik Sreedhar, Vivian Liu +3
Large language models (LLMs) are remarkably good at writing code. A particularly valuable case of human-LLM collaboration is code-based UI prototyping, a method for creating intera…
Simulating Human Strategic Behavior: Comparing Single and Multi-agent LLMs
Karthik Sreedhar, Lydia Chilton
When creating policies, plans, or designs for people, it is challenging for designers to foresee all of the ways in which people may reason and behave. Recently, Large Language Mod…