SOTAVerified

Transforming Scholarly Landscapes: Influence of Large Language Models on Academic Fields beyond Computer Science

2024-09-29Code Available0· sign in to hype

Aniket Pramanick, Yufang Hou, Saif M. Mohammad, Iryna Gurevych

Code Available — Be the first to reproduce this paper.

Reproduce

Code

Abstract

Large Language Models (LLMs) have ushered in a transformative era in Natural Language Processing (NLP), reshaping research and extending NLP's influence to other fields of study. However, there is little to no work examining the degree to which LLMs influence other research fields. This work empirically and systematically examines the influence and use of LLMs in fields beyond NLP. We curate 106 LLMs and analyze 45\% of LLM citations. Our findings further indicate that most of these fields predominantly employ task-agnostic LLMs, proficient in zero or few-shot learning without requiring further fine-tuning, to address their domain-specific problems. This study sheds light on the cross-disciplinary impact of NLP through LLMs, providing a better understanding of the opportunities and challenges.

Tasks

Reproductions