GPT 4
GPT-4, a large language model, is being extensively researched for its capabilities across diverse tasks, including translation, code analysis, educational assessment, and medical information extraction. Current research focuses on evaluating its performance against human benchmarks, exploring its limitations (e.g., susceptibility to prompt engineering and inconsistencies in complex reasoning), and developing methods to improve its reliability and efficiency, including the use of prompt engineering and ensemble methods with other machine learning models. These investigations are crucial for understanding GPT-4's strengths and weaknesses, informing its responsible deployment in various applications, and advancing the broader field of large language model development.
Papers
GPT-4 as an Effective Zero-Shot Evaluator for Scientific Figure Captions
Ting-Yao Hsu, Chieh-Yang Huang, Ryan Rossi, Sungchul Kim, C. Lee Giles, Ting-Hao K. Huang
Exploring the Boundaries of GPT-4 in Radiology
Qianchu Liu, Stephanie Hyland, Shruthi Bannur, Kenza Bouzid, Daniel C. Castro, Maria Teodora Wetscherek, Robert Tinn, Harshita Sharma, Fernando Pérez-García, Anton Schwaighofer, Pranav Rajpurkar, Sameer Tajdin Khanna, Hoifung Poon, Naoto Usuyama, Anja Thieme, Aditya V. Nori, Matthew P. Lungren, Ozan Oktay, Javier Alvarez-Valle
Dobby: A Conversational Service Robot Driven by GPT-4
Carson Stark, Bohkyung Chun, Casey Charleston, Varsha Ravi, Luis Pabon, Surya Sunkari, Tarun Mohan, Peter Stone, Justin Hart
GPT-4 as an Agronomist Assistant? Answering Agriculture Exams Using Large Language Models
Bruno Silva, Leonardo Nunes, Roberto Estevão, Vijay Aski, Ranveer Chandra