1 citations · 1 across the 3 of their papers we have counts for
3 papers
cs.CL2026★ 1 cited
Ministral 3
Alexander H. Liu, Kartik Khandelwal, Sandeep Subramanian +116
We introduce the Ministral 3 series, a family of parameter-efficient dense language models designed for compute and memory constrained applications, available in three model sizes:…
cs.LG2025
Not All Explanations for Deep Learning Phenomena Are Equally Valuable
Alan Jeffares, Mihaela van der Schaar
Developing a better understanding of surprising or counterintuitive phenomena has constituted a significant portion of deep learning research in recent years. These include double…
cs.LG2025
An Introduction to Discrete Variational Autoencoders
Alan Jeffares, Liyuan Liu
Variational Autoencoders (VAEs) are well-established as a principled approach to probabilistic unsupervised learning with neural networks. Typically, an encoder network defines the…