activity
20182026
most citedFair Learning with Private Demographic Data

26 citations · 122 across the 24 of their papers we have counts for

collaborators
Showing 2025Show all

5 papers · 1 filter

cs.MA2025

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…

cs.AI2025★ 3 cited

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…

cs.MA2025

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…

cs.HC2025

CodingGenie: A Proactive LLM-Powered Programming Assistant

Sebastian Zhao, Alan Zhu, Hussein Mozannar +3

While developers increasingly adopt tools powered by large language models (LLMs) in day-to-day workflows, these tools still require explicit user invocation. To seamlessly integra…

cs.CL2025★ 2 cited

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…