NeurIPS 2024 Workshop on Fine-tuning!

[Fanghui Liu]

Working on fine-tuning (of large language models or other models) in theory and/or practice? 

Consider submitting your paper to the 1st Workshop on Fine-Tuning in Modern Machine Learning: Principles and Scalability (FITML) at NeurIPS 2024 in Vancouver!

Website details: https://sites.google.com/view/neurips2024-ftw/home

OpenReview submission portal: https://openreview.net/group?id=NeurIPS.cc/2024/Workshop/FITML

Important dates (AoE time):

• Submission Deadline: September 15th, 2024, AoE
• Author notification: October 9th, 2024, AoE
• Workshop Date: December 14 or 15, 2024

Topics: include but are not limited to:

• New methodology for fine-tuning of various strategies, architectures and systems, from low-rank representation to sparse representation, from deep neural networks to LLMs, from algorithmic design to hardware design.
• Theoretical foundations of fine-tuning, e.g. approximation, optimization, and generalization from the perspective of transfer learning, deep learning theory, RLHF. Besides, theoretical understanding of low-rank representation from sketching and signal recovery are also welcome.
• New experimental observations that can help advance our understanding of the underlying mechanisms of fine-tuning, a discrepancy between existing theoretical analyses and practice, explainability and interpretability of fine-tuning in scientific contexts.

Awards: Among exceptional research papers with high review scores, we will select one best paper award, two runner-ups, and best poster award.

For other information about our workshop, please visit: https://sites.google.com/view/neurips2024-ftw/home

If you have any questions about paper submission and the workshop, please send email to: neurips...@outlook.com

We look forward to your contributions!