9 citations · 17 across the 6 of their papers we have counts for
6 papers
Inducing Task Models from Computer-Use Traces
Yucheng Jiang, Zora Zhiruo Wang, Ruishi Chen +1
Naturalistic computer-use traces, passively recorded screenshots and mouse or keyboard actions, are a valuable resource for deriving symbolic, auditable, and reusable models of how…
DataSTORM: Deep Research on Large-Scale Databases using Exploratory Data Analysis and Data Storytelling
Shicheng Liu, Yucheng Jiang, Sajid Farook +3
Deep research with Large Language Model (LLM) agents is emerging as a powerful paradigm for multi-step information discovery, synthesis, and analysis. However, existing approaches…
Future of Work with AI Agents: Auditing Automation and Augmentation Potential across the U.S. Workforce
Yijia Shao, Humishka Zope, Yucheng Jiang +4
The rapid rise of compound AI systems (a.k.a., AI agents) is reshaping the labor market, raising concerns about job displacement, diminished human agency, and overreliance on autom…
Collaborative Gym: A Framework for Enabling and Evaluating Human-Agent Collaboration
Yijia Shao, Vinay Samuel, Yucheng Jiang +2
While the advancement of large language models has spurred the development of AI agents to automate tasks, numerous use cases inherently require agents to collaborate with humans d…
Into the Unknown Unknowns: Engaged Human Learning through Participation in Language Model Agent Conversations
Yucheng Jiang, Yijia Shao, Dekun Ma +2
While language model (LM)-powered chatbots and generative search engines excel at answering concrete queries, discovering information in the terrain of unknown unknowns remains cha…
Assisting in Writing Wikipedia-like Articles From Scratch with Large Language Models
Yijia Shao, Yucheng Jiang, Theodore A. Kanell +3
We study how to apply large language models to write grounded and organized long-form articles from scratch, with comparable breadth and depth to Wikipedia pages. This underexplore…