1 code implementation • 9 Mar 2024 • Jie Liu, Zhongyuan Zhao, Zijian Ding, Benjamin Brock, Hongbo Rong, Zhiru Zhang
The ongoing trend of hardware specialization has led to a growing use of custom data formats when processing sparse workloads, which are typically memory-bound.
no code implementations • 13 Feb 2024 • Zijian Ding, Joel Chan
Complex data analysis inherently seeks unexpected insights through exploratory visual analysis methods, transcending logical, step-by-step processing.
1 code implementation • 16 Oct 2023 • Zijian Ding, Alison Smith-Renner, Wenjuan Zhang, Joel R. Tetreault, Alejandro Jaimes
To explore how humans can best leverage LLMs for writing and how interacting with these models affects feelings of ownership and trust in the writing process, we compared common human-AI interaction types (e. g., guiding system, selecting from system outputs, post-editing outputs) in the context of LLM-assisted news headline generation.
no code implementations • 21 Aug 2023 • Chen Cao, Zijian Ding, Gyeong-Geon Lee, Jiajun Jiao, Jionghao Lin, Xiaoming Zhai
Our study demonstrates the potential of applying large language models to educational practice on STEM subjects.
no code implementations • 8 Aug 2023 • Cassie Chen Cao, Zijian Ding, Jionghao Lin, Frank Hopfgartner
This study investigates the use of Artificial Intelligence (AI)-powered, multi-role chatbots as a means to enhance learning experiences and foster engagement in computer science education.
no code implementations • 11 Mar 2023 • Zijian Ding, Joel Chan
Large Language Models (LLMs) have demonstrated impressive text generation capabilities, prompting us to reconsider the future of human-AI co-creation and how humans interact with LLMs.
no code implementations • 27 Feb 2023 • Zijian Ding, Arvind Srinivasan, Stephen MacNeil, Joel Chan
Cross-domain analogical reasoning is a core creative ability that can be challenging for humans.
no code implementations • 16 Feb 2022 • Zijian Ding, Jiawen Kang, Tinky Oi Ting HO, Ka Ho Wong, Helene H. Fung, Helen Meng, Xiaojuan Ma
This is used in the development of TalkTive, a CA which can predict both timing and form of backchanneling during cognitive assessments.