activity
20182026
most citedInteractive Debugging and Steering of Multi-Agent AI Systems

30 citations · 112 across the 17 of their papers we have counts for

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7 papers · 1 filter

cs.AI2026

Agents in the Wild: Where Research Meets Deployment

Grace Hui Yang, Pranav N. Venkit, Hooman Sedghamiz +3

Agentic systems large language model (LLM) based architectures capable of reasoning, planning, acting, and coordinating with tools and other agents are rapidly transitioning from r…

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.AI2024★ 15 cited

Magentic-One: A Generalist Multi-Agent System for Solving Complex Tasks

Adam Fourney, Gagan Bansal, Hussein Mozannar +17

Modern AI agents, driven by advances in large foundation models, promise to enhance our productivity and transform our lives by augmenting our knowledge and capabilities. To achiev…

cs.AI2024★ 4 cited

Data Analysis in the Era of Generative AI

Jeevana Priya Inala, Chenglong Wang, Steven Drucker +6

This paper explores the potential of AI-powered tools to reshape data analysis, focusing on design considerations and challenges. We explore how the emergence of large language and…

cs.AI2024

Concept Distillation from Strong to Weak Models via Hypotheses-to-Theories Prompting

Emmanuel Aboah Boateng, Cassiano O. Becker, Nabiha Asghar +5

Hand-crafting high quality prompts to optimize the performance of language models is a complicated and labor-intensive process. Furthermore, when migrating to newer, smaller, or we…

cs.AI2023

Axiomatic Preference Modeling for Longform Question Answering

Corby Rosset, Guoqing Zheng, Victor Dibia +2

The remarkable abilities of large language models (LLMs) like GPT-4 partially stem from post-training processes like Reinforcement Learning from Human Feedback (RLHF) involving hum…

cs.AI2023★ 9 cited

LIDA: A Tool for Automatic Generation of Grammar-Agnostic Visualizations and Infographics using Large Language Models

Victor Dibia

Systems that support users in the automatic creation of visualizations must address several subtasks - understand the semantics of data, enumerate relevant visualization goals and…