For details, please see the webpage: https://sites.google.com/servicenow.com/good-data-2025/

Foundation models highly depend on the data they are trained on. Although self-supervised learning is one of their promises, it is clear that the carefully processed datasets lead to better models. While datasets and models are frequently released by the community, the data preparation recipes are relatively nascent and not fully open. In this workshop, we invite contributions and collaborations in data preparation recipes for creating and using foundation models and generative AI applications, including (but not limited to) pre-training, alignment, fine tuning, and in-context learning. Data preparation spans data acquisition, cleaning, processing, mixtures, quality assessments, value of data, ablation studies, safety, and governance.

# Important Dates
▪ Workshop paper submission deadline: 20 November 2024, 11:59 pm AoE.
▪ Notification to authors: 9 December 2024.
▪ Date of workshop: 3 or 4 March 2025.

# Topics
We encourage submissions under one of these topics of interest, but we also welcome other interesting and relevant research for preparing good data.
▪ Data acquisition, cleaning, processing, and mixture recipes
▪ Data quality assessment and quantifying the value of data
▪ Data sequence for multi-phase and curriculum learning
▪ Model-based data improvement techniques
▪ Ablation study strategies to understand the interplay between data and model
▪ Data safety and governance
▪ Responsible and ethical considerations of data collection and human annotation
▪ Diversity, bias, transparency, and privacy of data
▪ Theoretical modeling and analysis of data-related aspects in generative AI
▪ Large-scale data processing (intersection between systems and algorithms)
▪ Data value

We accept submissions of a maximum of 4 pages (excluding references and appendix). Papers will be peer-reviewed under a double-blind policy. Accepted papers will be presented at the poster session, some as oral presentations, and one paper will be awarded as the best paper.

# OpenReview Submission Link
Please submit your paper via the following link: https://openreview.net/group?id=AAAI.org/2025/Workshop/GoodData

# Submission Guidelines
▪ We accept submissions of a maximum of 4 pages (excluding references and appendix).
▪ We accept only original works not published before at any archival venue with proceedings.
▪ The submitted manuscript should follow the AAAI 2025 paper template.
▪ Submissions will be rejected without review if they:
▪ Contain more than 4 pages (excluding references and appendix).
▪ Violate the double-blind policy.
▪ Violate the dual-submission policy for papers.
▪ The accepted papers will be publicly accessible on OpenReview, but the workshop is non-archival and does not have formal proceedings.
▪ Papers will be peer-reviewed under a double-blind policy and must be submitted online through the OpenReview submission system.