ChatGPT Generated Conversation
Research on ChatGPT-generated conversations explores how this large language model (LLM) performs in various interactive contexts, focusing on its capabilities, limitations, and potential biases. Current studies investigate its application in diverse fields, including education (e.g., essay scoring, literature review assistance), healthcare (e.g., medication management, robot interaction), and software development (e.g., code generation, library recommendation), often comparing its performance to human experts or other AI models. This work is significant because it helps assess the reliability and ethical implications of LLMs in real-world applications, informing the development of responsible AI and highlighting potential risks and benefits across numerous sectors.
Papers
A Preliminary Evaluation of ChatGPT for Zero-shot Dialogue Understanding
Wenbo Pan, Qiguang Chen, Xiao Xu, Wanxiang Che, Libo Qin
Extractive Summarization via ChatGPT for Faithful Summary Generation
Haopeng Zhang, Xiao Liu, Jiawei Zhang
Can ChatGPT and Bard Generate Aligned Assessment Items? A Reliability Analysis against Human Performance
Abdolvahab Khademi
Should ChatGPT be Biased? Challenges and Risks of Bias in Large Language Models
Emilio Ferrara
What does ChatGPT return about human values? Exploring value bias in ChatGPT using a descriptive value theory
Ronald Fischer, Markus Luczak-Roesch, Johannes A Karl
Evaluating the Logical Reasoning Ability of ChatGPT and GPT-4
Hanmeng Liu, Ruoxi Ning, Zhiyang Teng, Jian Liu, Qiji Zhou, Yue Zhang
ChatGPT-Crawler: Find out if ChatGPT really knows what it's talking about
Aman Rangapur, Haoran Wang
When do you need Chain-of-Thought Prompting for ChatGPT?
Jiuhai Chen, Lichang Chen, Heng Huang, Tianyi Zhou
Investigating Chain-of-thought with ChatGPT for Stance Detection on Social Media
Bowen Zhang, Xianghua Fu, Daijun Ding, Hu Huang, Genan Dai, Nan Yin, Yangyang Li, Liwen Jing
ChatGPT: More than a Weapon of Mass Deception, Ethical challenges and responses from the Human-Centered Artificial Intelligence (HCAI) perspective
Alejo Jose G. Sison, Marco Tulio Daza, Roberto Gozalo-Brizuela, Eduardo C. Garrido-Merchán
Can Large Language Models Play Text Games Well? Current State-of-the-Art and Open Questions
Chen Feng Tsai, Xiaochen Zhou, Sierra S. Liu, Jing Li, Mo Yu, Hongyuan Mei
Summary of ChatGPT-Related Research and Perspective Towards the Future of Large Language Models
Yiheng Liu, Tianle Han, Siyuan Ma, Jiayue Zhang, Yuanyuan Yang, Jiaming Tian, Hao He, Antong Li, Mengshen He, Zhengliang Liu, Zihao Wu, Lin Zhao, Dajiang Zhu, Xiang Li, Ning Qiang, Dingang Shen, Tianming Liu, Bao Ge
Is ChatGPT a Highly Fluent Grammatical Error Correction System? A Comprehensive Evaluation
Tao Fang, Shu Yang, Kaixin Lan, Derek F. Wong, Jinpeng Hu, Lidia S. Chao, Yue Zhang
One Small Step for Generative AI, One Giant Leap for AGI: A Complete Survey on ChatGPT in AIGC Era
Chaoning Zhang, Chenshuang Zhang, Chenghao Li, Yu Qiao, Sheng Zheng, Sumit Kumar Dam, Mengchun Zhang, Jung Uk Kim, Seong Tae Kim, Jinwoo Choi, Gyeong-Moon Park, Sung-Ho Bae, Lik-Hang Lee, Pan Hui, In So Kweon, Choong Seon Hong
To ChatGPT, or not to ChatGPT: That is the question!
Alessandro Pegoraro, Kavita Kumari, Hossein Fereidooni, Ahmad-Reza Sadeghi
Safety Analysis in the Era of Large Language Models: A Case Study of STPA using ChatGPT
Yi Qi, Xingyu Zhao, Siddartha Khastgir, Xiaowei Huang
Exploring the Use of Large Language Models for Reference-Free Text Quality Evaluation: An Empirical Study
Yi Chen, Rui Wang, Haiyun Jiang, Shuming Shi, Ruifeng Xu