no code implementations • 18 Mar 2024 • Andrew Katz, Mitchell Gerhardt, Michelle Soledad
Unfortunately, when there is a lot of feedback from multiple sources, it can be difficult to distill the information into actionable insights.
no code implementations • 9 May 2023 • Andrew Katz, Siqing Wei, Gaurav Nanda, Christopher Brinton, Matthew Ohland
This study contributes to the growing body of research on the use of AI models in educational contexts and highlights the potential of ChatGPT for facilitating analysis of student comments.
no code implementations • 26 Sep 2020 • Chenhan Yuan, Ryan Rossi, Andrew Katz, Hoda Eldardiry
In this paper, we relax this strong assumption by a weaker distant supervision assumption to address the second issue and propose a novel sentence distribution estimator model to address the first problem.
no code implementations • 26 Sep 2020 • Chenhan Yuan, Ryan Rossi, Andrew Katz, Hoda Eldardiry
To address this issue, we propose a Clustering-based Unsupervised generative Relation Extraction (CURE) framework that leverages an "Encoder-Decoder" architecture to perform self-supervised learning so the encoder can extract relation information.