178 citations · 243 across the 11 of their papers we have counts for
6 papers · 1 filter
Magentic Marketplace: An Open-Source Environment for Studying Agentic Markets
Gagan Bansal, Wenyue Hua, Zezhou Huang +21
As LLM agents advance, they are increasingly mediating economic decisions, ranging from product discovery to transactions, on behalf of users. Such applications promise benefits bu…
Magentic-UI: Towards Human-in-the-loop Agentic Systems
Hussein Mozannar, Gagan Bansal, Cheng Tan +17
AI agents powered by large language models are increasingly capable of autonomously completing complex, multi-step tasks using external tools. Yet, they still fall short of human-l…
Optimizing Sequential Multi-Step Tasks with Parallel LLM Agents
Enhao Zhang, Erkang Zhu, Gagan Bansal +3
Large language model (LLM)-based multi-agent systems have demonstrated remarkable promise for tackling complex tasks by breaking them down into subtasks that are iteratively planne…
Interactive Debugging and Steering of Multi-Agent AI Systems
Will Epperson, Gagan Bansal, Victor Dibia +4
Fully autonomous teams of LLM-powered AI agents are emerging that collaborate to perform complex tasks for users. What challenges do developers face when trying to build and debug…
Navigating Rifts in Human-LLM Grounding: Study and Benchmark
Omar Shaikh, Hussein Mozannar, Gagan Bansal +2
Language models excel at following instructions but often struggle with the collaborative aspects of conversation that humans naturally employ. This limitation in grounding -- the…
Measuring AI agent autonomy: Towards a scalable approach with code inspection
Peter Cihon, Merlin Stein, Gagan Bansal +2
AI agents are AI systems that can achieve complex goals autonomously. Assessing the level of agent autonomy is crucial for understanding both their potential benefits and risks. Cu…