[ACL23Demo] PersLEARN: Research Training through the Lens of Perspective Cultivation

Abstract

Scientific research is inherently shaped by its authors’ perspectives, influenced by various factors such as their personality, community, or society. Junior researchers often face challenges in identifying the perspectives reflected in the existing literature and struggle to develop their own viewpoints. In response to this issue, we introduce PersLEARN, a tool designed to facilitate the cultivation of scientific perspectives, starting from a basic seed idea and progressing to a well-articulated framework. By interacting with a prompt-based model, researchers can develop their perspectives explicitly. Our human study reveals that scientific perspectives developed by students using PersLEARN exhibit a superior level of logical coherence and depth compared to those that did not. Furthermore, our pipeline outperforms baseline approaches across multiple domains of literature from various perspectives. These results suggest that PersLEARN could help foster a greater appreciation of diversity in scientific perspectives as an essential component of research training.

Publication
In Proceedings of the Association for Computational Linguistics System Demonstrations
Shiqian Li
Shiqian Li
Ph.D. '22
Lecheng Ruan
Lecheng Ruan
Research Professor
Yuxi Ma (Yuki)
Yuxi Ma (Yuki)
Ph.D. '24

My research interests include psychology-inspired AI research to understand and model human behavior and cognition, as well as investigating machine creativity and its applications in art.

Yixin Zhu
Yixin Zhu
Assistant Professor

I build humanlike AI.