The 2024 NeurIPS Workshop on Fine-Tuning in Modern Machine Learning: Principles and Scalability calls for 4-8 pages paper (references and appendix not included) of high-quality contributions on algorithmic advance, mathmetical foundation, empirical observations of fine-tuning. 

LaTeX style file: Overleaf Teamplate or GoogleDrive or download (NeurIPS'24 template). ICLR'25 template is also allowable. NB: The page limit for the main text is with 4-8 pages

Key topics include but are not limited to:

The topics are not limited to fine-tuning, LLMs. Any topic on theoretical and/or empricial results for understanding and advancing modern practices for efficiency in machine learning is also welcome.