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
Is GPT-4 a Good Data Analyst?
Liying Cheng, Xingxuan Li, Lidong Bing
Towards Reliable Misinformation Mitigation: Generalization, Uncertainty, and GPT-4
Kellin Pelrine, Anne Imouza, Camille Thibault, Meilina Reksoprodjo, Caleb Gupta, Joel Christoph, Jean-François Godbout, Reihaneh Rabbany
Leveraging GPT-4 for Automatic Translation Post-Editing
Vikas Raunak, Amr Sharaf, Yiren Wang, Hany Hassan Awadallah, Arul Menezes
DecipherPref: Analyzing Influential Factors in Human Preference Judgments via GPT-4
Yebowen Hu, Kaiqiang Song, Sangwoo Cho, Xiaoyang Wang, Hassan Foroosh, Fei Liu
Evaluating GPT-4 and ChatGPT on Japanese Medical Licensing Examinations
Jungo Kasai, Yuhei Kasai, Keisuke Sakaguchi, Yutaro Yamada, Dragomir Radev
GPT-4 can pass the Korean National Licensing Examination for Korean Medicine Doctors
Dongyeop Jang, Tae-Rim Yun, Choong-Yeol Lee, Young-Kyu Kwon, Chang-Eop Kim