[47] Vivian Lai, Samuel Carton, Rajat Bhatnagar, Q Vera Liao, Yunfeng Zhang, and Chenhao Tan. Human-ai collaboration via conditional delegation: A case study of content moderation. In CHI Conference on Human Factors in Computing Systems, pages 1–18, 2022.
[48] Tsung-Yi Lin, Michael Maire, Serge Belongie, James Hays, Pietro Perona, Deva Ramanan, Piotr Dólár, and C Lawrence Zitnick. Microsoft coco: Common objects in context. In Computer Vision-ECCV 2014: 13th European Conference, Zurich, Switzerland, September 6-12, 2014, Proceedings, Part V 13, pages 740-755. Springer, 2014.
[49] Han Liu, Vivian Lai, and Chenhao Tan. Understanding the effect of out-of-distribution examples and interactive explanations on human-ai decision making. Proceedings of the ACM on Human-Computer Interaction, 5(CSCW2):1-45, 2021.
[50] Gaifang Luo, Lijun Cheng, Chao Jing, Can Zhao, and Guozhu Song. A thorough review of models, evaluation metrics, and datasets on image captioning. IET Image Processing, 16(2): 311-332, 2022.
[51] Shuai Ma, Ying Lei, Xinru Wang, Chengbo Zheng, Chuhan Shi, Ming Yin, and Xiaojuan Ma. Who should i trust: Ai or myself? leveraging human and ai correctness likelihood to promote appropriate trust in ai-assisted decision-making. arXiv preprint arXiv:2301.05809, 2023.
[52] David Madras, Toni Pitassi, and Richard Zemel. Predict responsibly: Improving fairness and accuracy by learning to defer. In Advances in Neural Information Processing Systems, pages 6150-6160, 2018.
[53] Zainy M Malakan, Ghulam Mubashar Hassan, and Ajmal Mian. Vision transformer based model for describing a set of images as a story. In AI 2022: Advances in Artificial Intelligence: 35th Australasian Joint Conference, AI 2022, Perth, WA, Australia, December 5-8, 2022, Proceedings, pages 15-28. Springer, 2022.
[54] Todor Mihaylov, Peter Clark, Tushar Khot, and Ashish Sabharwal. Can a suit of armor conduct electricity? a new dataset for open book question answering. arXiv preprint arXiv:1809.02789, 2018.
[55] Margaret Mitchell, Simone Wu, Andrew Zaldivar, Parker Barnes, Lucy Vasserman, Ben Hutchinson, Elena Spitzer, Inioluwa Deborah Raji, and Timnit Gebru. Model cards for model reporting. In Proceedings of the conference on fairness, accountability, and transparency, pages 220–229, 2019.
[56] Hussein Mozannar and David Sontag. Consistent estimators for learning to defer to an expert. In International Conference on Machine Learning, pages 7076-7087. PMLR, 2020.
[57] Hussein Mozannar, Arvind Satyanarayan, and David Sontag. Teaching humans when to defer to a classifier via exemplars. In Proceedings of the AAAI Conference on Artificial Intelligence, volume 36, pages 5323-5331, 2022.
[58] Hussein Mozannar, Hunter Lang, Dennis Wei, Prasanna Sattigeri, Subhro Das, and David Sontag. Who should predict? exact algorithms for learning to defer to humans. In International Conference on Artificial Intelligence and Statistics, pages 10520-10545. PMLR, 2023.
[59] OpenAI. Chatgpt: Introducing chatgpt. https://openai.com/blog/chatgpt, 2022.
[60] Lucy Portnoff, Erin Gustafson, Joseph Rollinson, and Klinton Bicknell. Methods for language learning assessment at scale: Duolingo case study. International Educational Data Mining Society, 2021.
[61] Christopher Potts, Zhengxuan Wu, Atticus Geiger, and Douwe Kiela. Dynasent: A dynamic benchmark for sentiment analysis. arXiv preprint arXiv:2012.15349, 2020.
[62] Alec Radford, Jong Wook Kim, Chris Hallacy, Aditya Ramesh, Gabriel Goh, Sandhini Agarwal, Girish Sastry, Amanda Askell, Pamela Mishkin, Jack Clark, et al. Learning transferable visual models from natural language supervision. In International conference on machine learning, pages 8748-8763. PMLR, 2021.