ChatGPT 4 Outperforms Expert
Recent research demonstrates that large language models, particularly ChatGPT and its variants, are achieving performance comparable to, and in some cases exceeding, that of human experts in various tasks. Studies focus on adapting these models for applications like medical diagnosis, educational assessment, and social science data analysis, often involving fine-tuning on specific datasets to improve accuracy and reduce bias. This surpasses the capabilities previously thought to be uniquely human, highlighting the potential for LLMs to significantly enhance efficiency and accuracy across diverse fields. However, concerns remain regarding potential misuse, such as in creating sophisticated phishing attacks, emphasizing the need for responsible development and deployment.
Papers
Phoenix: Democratizing ChatGPT across Languages
Zhihong Chen, Feng Jiang, Junying Chen, Tiannan Wang, Fei Yu, Guiming Chen, Hongbo Zhang, Juhao Liang, Chen Zhang, Zhiyi Zhang, Jianquan Li, Xiang Wan, Benyou Wang, Haizhou Li
Can ChatGPT Reproduce Human-Generated Labels? A Study of Social Computing Tasks
Yiming Zhu, Peixian Zhang, Ehsan-Ul Haq, Pan Hui, Gareth Tyson