Machine Learning Done Right.

Exploring Diffusion Transformer Designs via Grafting

Keshigeyan Chandrasegaran, Michael Poli

How Effectively Does a Model Use Its Memory

Rom Parnichkun, Neehal Tumma, Stefano Massaroli, Michael Poli, Armin Thomas, Liquid Team

Convolutional Multi-Hybrids for Edge Devices

Armin Thomas, Stefano Massaroli, Michael Poli, Liquid Edge Team

Automated Architecture Synthesis via Targeted Evolution

Armin W. Thomas, Rom Parnichkun, Alexander Amini, Stefano Massaroli and Michael Poli

LFM-1B-Math: Can Small Models Be Concise Reasoners?

Tim Seyde, Rohin Manvi, Maxime Labonne, Liquid AI Team

From Liquid Neural Networks to Liquid Foundation Models

Expressive Sign Equivariant Networks for Spectral Geometric Learning

Derek Lim, Joshua Robinson, Stefanie Jegelka, Haggai Maron

Convolutional State Space Models for Long-Range Spatiotemporal Modeling

Jimmy T.H. Smith, Shalini De Mello, Jan Kautz, Scott Linderman, Wonmin Byeon

Improving *day-ahead* Solar Irradiance Time Series Forecasting by Leveraging Spatio-Temporal Context

Oussama Boussif, Ghait Boukachab, Dan Assouline, Stefano Massaroli, Tianle Yuan, Loubna Benabbou, Yoshua Bengio

HyenaDNA: Long-Range Genomic Sequence Modeling at Single Nucleotide Resolution

Eric Nguyen, Michael Poli, Marjan Faizi, Armin W Thomas, Michael Wornow, Callum Birch-Sykes, Stefano Massaroli, Aman Patel, Clayton M. Rabideau, Yoshua Bengio, Stefano Ermon, Christopher Re, Stephen Baccus

Learning Efficient Surrogate Dynamic Models with Graph Spline Networks

Chuanbo Hua, Federico Berto, Michael Poli, Stefano Massaroli, Jinkyoo Park

DiffuseBot: Breeding Soft Robots With Physics-Augmented Generative Diffusion Models

Tsun-Hsuan Wang, Juntian Zheng, Pingchuan Ma, Yilun Du, Byungchul Kim, Andrew Everett Spielberg, Joshua B. Tenenbaum, Chuang Gan, Daniela Rus

Laughing Hyena Distillery: Extracting Compact Recurrences From Convolutions

Stefano Massaroli, Michael Poli, Daniel Y Fu, Hermann Kumbong, Rom Nishijima Parnichkun, David W. Romero, Aman Timalsina, Quinn McIntyre, Beidi Chen, Atri Rudra, Ce Zhang, Christopher Re, Stefano Ermon, Yoshua Bengio

On the Size and Approximation Error of Distilled Datasets

Alaa Maalouf, Murad Tukan, Noel Loo, Ramin Hasani, Mathias Lechner, Daniela Rus

Compositional Policy Learning in Stochastic Control Systems with Formal Guarantees

Đorđe Žikelić, Mathias Lechner, Abhinav Verma, Krishnendu Chatterjee, Thomas A Henzinger