21 citations · 30 across the 7 of their papers we have counts for
8 papers
Learning to GUIDE the Group: Self-Learning LLM Facilitation Across Multi-Party Tasks
Ziyi Liu, Tzu-Sheng Kuo, Jiale Liu +3
As large language models are increasingly adopted as multi-party communication facilitators, there is a growing demand for agents capable of balancing diverse group dynamics across…
Real-Time Group Dynamics with LLM Facilitation: Evidence from a Charity Allocation Task
Aaron Parisi, Nithum Thain, Alden Hallak +2
As large language models (LLMs) evolve from single-user assistants to active participants in civic and workplace deliberation, evaluating their effects on collective decision makin…
Choose Your Agent: Tradeoffs in Adopting AI Advisors, Coaches, and Delegates in Multi-Party Negotiation
Kehang Zhu, Nithum Thain, Vivian Tsai +2
As AI usage becomes more prevalent in social contexts, understanding agent-user interaction is critical to designing systems that imp rove both individual and group outcomes. We pr…
Strategic Tradeoffs Between Humans and AI in Multi-Agent Bargaining
Crystal Qian, Kehang Zhu, John Horton +4
Markets increasingly accommodate large language models (LLMs) as autonomous decision-making agents. As this transition occurs, it becomes critical to evaluate how these agents beha…
The Evolution of LLM Adoption in Industry Data Curation Practices
Crystal Qian, Michael Xieyang Liu, Emily Reif +7
As large language models (LLMs) grow increasingly adept at processing unstructured text data, they offer new opportunities to enhance data curation workflows. This paper explores t…
Take It, Leave It, or Fix It: Measuring Productivity and Trust in Human-AI Collaboration
Crystal Qian, James Wexler
Although recent developments in generative AI have greatly enhanced the capabilities of conversational agents such as Google's Gemini (formerly Bard) or OpenAI's ChatGPT, it's uncl…
Understanding the Dataset Practitioners Behind Large Language Model Development
Crystal Qian, Emily Reif, Minsuk Kahng
As large language models (LLMs) become more advanced and impactful, it is increasingly important to scrutinize the data that they rely upon and produce. What is it to be a dataset…
Automatic Histograms: Leveraging Language Models for Text Dataset Exploration
Emily Reif, Crystal Qian, James Wexler +1
Making sense of unstructured text datasets is perennially difficult, yet increasingly relevant with Large Language Models. Data workers often rely on dataset summaries, especially…