Comparative Analysis of OpenAI GPT-4o and DeepSeek R1 for Scientific Text Categorization Using Prompt Engineering
Year: 2025
Type: conference-paper
Abstract: This study examines how large language models categorize sentences from scientific papers using prompt engineering.We use two advanced web-based models, OpenAI's GPT-4o and DeepSeek R1, to classify sentences into predefined relationship categories.DeepSeek R1 has been tested on benchmark datasets in its technical report.However, its performance in scientific text categorization remains unexplored.To address this gap, we introduce a new evaluation method designed specifically for this task.We also compile a dataset of cleaned scientific papers from diverse domains.This dataset provides a platform for comparing the two models.Using this dataset, we analyze their effectiveness and consistency in categorization.
DOI: 10.18260/1-2--54654
Authors: Aniruddha Maiti, Samuel Adewumi, TEMESGEN TIKURE, Zichun Wang, Niladri Sengupta, Anastasiia Sukhanova, Ananya Jana
Institutions: West Virginia State University, Marshall University
Language: English
Topic: Topic Modeling
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: bronze
OpenAlex ID: W4409945337