no code implementations • 13 Jan 2024 • Zhuoran Lu, Dakuo Wang, Ming Yin
AI assistance in decision-making has become popular, yet people's inappropriate reliance on AI often leads to unsatisfactory human-AI collaboration performance.
no code implementations • 11 Jan 2024 • Zhuoyan Li, Zhuoran Lu, Ming Yin
In this paper, we propose a computational framework that can provide an interpretable characterization of the influence of different forms of AI assistance on decision makers in AI-assisted decision making.
no code implementations • 15 Nov 2023 • Sheshera Mysore, Zhuoran Lu, Mengting Wan, Longqi Yang, Steve Menezes, Tina Baghaee, Emmanuel Barajas Gonzalez, Jennifer Neville, Tara Safavi
Powerful large language models have facilitated the development of writing assistants that promise to significantly improve the quality and efficiency of composition and communication.
no code implementations • 11 Oct 2023 • Zhuoyan Li, Hangxiao Zhu, Zhuoran Lu, Ming Yin
The collection and curation of high-quality training data is crucial for developing text classification models with superior performance, but it is often associated with significant costs and time investment.