Are you interested in the latest developments in machine learning reproducibility? This month, Princeton University is hosting the 8th iteration of the Machine Learning Reproducibility Challenge (MLRC) on August 21st. The event features an impressive lineup of keynote speakers, including Arvind Narayanan from Princeton, Soumith Chintala from Pytorch-Meta, Jonathan Frankle from Databricks, and Stella Biderman from EleutherAI.
One of the highlight sessions is a panel discussion on the reproducibility of and by large language models, moderated by Sayash Kapoor from Princeton. If you’re interested in attending, you can still register on the MLRC website.
The MLRC 2025 challenge aims to bring together researchers, practitioners, and industry experts to tackle the pressing issue of reproducibility in machine learning. This event is a great opportunity to learn from the experts, network with like-minded individuals, and contribute to the advancement of machine learning research.
Will you be attending the MLRC 2025 challenge? Share your thoughts on the importance of reproducibility in machine learning.