CrossData: Leveraging Text-Data Connections for Authoring Data Documents. In CHI Conference on Human Factors in Computing Systems . ACM, 95:1–95:15
Chen Zhu-Tian and Haijun Xia. 2022 · 2022
Cited alongside, same era.
Sporthesia: Augmenting Sports Videos Using Natural Language
Chen Zhu-Tian, Qisen Yang, Xiao Xie, Johanna Beyer, Haijun Xia, Yingcai Wu, and Hanspeter Pfister. 2023 · 2022
Cited alongside, same era.
Spellburst: A Node-based Interface for Exploratory Creative Coding with Natural Language Prompts. In Proceedings of the 36th Annual ACM Symposium on User Interface Software and Technology . 1–22
Tyler Angert, Miroslav Suzara, Jenny Han, Christopher Pondoc, and Hariharan Subramonyam. 2023 · 2023
Cited alongside, same era.
Grounded copilot: How programmers interact with code-generating models
Shraddha Barke, Michael B James, and Nadia Polikarpova. 2023 · 2023
Cited alongside, same era.
Low-code LLM: Visual Programming over LLMs
Original
Yuzhe Cai, Shaoguang Mao, Wenshan Wu, Zehua Wang, Yaobo Liang, Tao Ge, Chenfei Wu, Wang You, Ting Song, Yan Xia, et al · 2023
Cited alongside, same era.
DataParticles: Block-based and Language-oriented Authoring of Animated Unit Visualizations. In CHI Conference on Human Factors in Computing Systems . ACM, 808:1–808:15
Yining Cao, Jane L. E, Chen Zhu-Tian, and Haijun Xia. 2023 · 2023
Cited alongside, same era.
Studying the effect of AI Code Generators on Supporting Novice Learners in Introductory Programming. In Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems (<conf-loc>, <city>Hamburg</city>, <country>Germany</country>, </conf-loc>) (CHI ’23) . Association for Computing Machinery, New York, NY, USA, Article 455, 23 pages
Majeed Kazemitabaar, Justin Chow, Carl Ka To Ma, Barbara J. Ericson, David Weintrop, and Tovi Grossman. 2023 · 2023
Cited alongside, same era.
A Large-Scale Survey on the Usability of AI Programming Assistants: Successes and Challenges
Original
Jenny T. Liang, Chenyang Yang, and Brad A. Myers. 2023 · 2023
Cited alongside, same era.
"What It Wants Me To Say": Bridging the Abstraction Gap Between End-User Programmers and Code-Generating Large Language Models. In Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems . 1–31
Michael Xieyang Liu, Advait Sarkar, Carina Negreanu, Benjamin Zorn, Jack Williams, Neil Toronto, and Andrew D Gordon. 2023a · 2023
Cited alongside, same era.
“What It Wants Me To Say”: Bridging the Abstraction Gap Between End-User Programmers and Code-Generating Large Language Models. In Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems (<conf-loc>, <city>Hamburg</city>, <country>Germany</country>, </conf-loc>) (CHI ’23) . Association for Computing Machinery, New York, NY, USA, Article 598, 31 pages
Michael Xieyang Liu, Advait Sarkar, Carina Negreanu, Benjamin Zorn, Jack Williams, Neil Toronto, and Andrew D. Gordon. 2023b · 2023
Cited alongside, same era.