The 4th International Workshop on Data-Centric AI will be held at CIKM 2024. In recent days, machine learning focuses on developing models for datasets, but real-world data is often messy. Improving the dataset itself can be a better way to enhance performance instead of just improving the models. Data-Centric AI (DCAI) is an emerging field that systematically improves datasets, resulting in significant improvements in ML applications. DCAI treats data improvement as an engineering discipline, offering a shift in focus from modeling to the underlying data. This workshop aims to build an interdisciplinary DCAI community to tackle data problems such as collection, labeling, preprocessing, quality evaluation, debt, and governance. Interested parties can shape the future of AI and ML by submitting papers in response to the call for papers. 

Submission Guidelines

We invite the submission of regular research papers (max 9 pages), including the bibliography and any possible appendices. Submissions must be in PDF format, and formatted according to the 2-column ACM sigconf template. Submitted papers will be assessed based on their novelty, technical quality, potential impact, insightfulness, depth, clarity, and reproducibility.

Committees

Program Committee

• Dongjie Wang
• Meng Xiao
• Pengfei Wang
• Kunpeng Liu
• Pengyang Wang
• Wangyang Ying
• Nanxu Gong
• Xinyuan Wang
• Ziyue Qiao

Organizing committee

• Hui Xiong
• Vipin Kumar
• Yanjie Fu
• Kunpeng Liu
• Pengyang Wang
• Pengfei Wang
• Dongjie Wang
• Meng Xiao 
• Yanyong Huang
• Wei Fan
• Ziyue Qiao
• Zhengzhang Chen

Contact

All questions about submissions should be emailed to kunpeng@pdx.edu