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

LFM2 Technical Report

Alexander Amini, Anna Banaszak, Harold Benoit, Arthur Böök, Tarek Dakhran, Song Duong, Alfred Eng, Fernando Fernandes, Marc Härkönen, Anne Harrington, Ramin Hasani, Saniya Karwa, Yuri Khrustalev, Maxime Labonne, Mathias Lechner, Valentine Lechner, Simon Lee, Zetian Li, Noel Loo, Jacob Marks, Edoardo Mosca, Samuel J. Paech, Paul Pak, Rom N. Parnichkun, Alex Quach, Ryan Rogers, Daniela Rus, Nayan Saxena, Bettina Schlager, Tim Seyde, Jimmy T.H. Smith, Aditya Tadimeti, Neehal Tumma

Towards a theory of learning dynamics in deep state space models

Jakub Smekal, Jimmy Smith, Michael Kleinman, Dan Biderman, Scott Linderman

The Empirical Impact of Neural Parameter Symmetries, or Lack Thereof

Derek Lim, Theo Putterman, Robin Walters, Haggai Maron, Stefanie Jegelka

State-Free Inference of State-Space Models: The *Transfer Function* Approach

Rom Parnichkun, Stefano Massaroli, Alessandro Moro, Jimmy T.H. Smith, Ramin Hasani, Mathias Lechner, Qi An, Christopher Re, Hajime Asama, Stefano Ermon, Taiji Suzuki, Michael Poli, Atsushi Yamashita

Mechanistic Design and Scaling of Hybrid Architectures

Michael Poli, Armin W Thomas, Eric Nguyen, Pragaash Ponnusamy, Björn Deiseroth, Kristian Kersting, Taiji Suzuki, Brian Hie, Stefano Ermon, Christopher Re, Ce Zhang, Stefano Massaroli

Position: Future Directions in the Theory of Graph Machine Learning

Christopher Morris, Fabrizio Frasca, Nadav Dym, Haggai Maron, Ismail Ilkan Ceylan, Ron Levie, Derek Lim, Michael M. Bronstein, Martin Grohe, Stefanie Jegelka

RoboGen: Towards Unleashing Infinite Data for Automated Robot Learning via Generative Simulation

Yufei Wang, Zhou Xian, Feng Chen, Tsun-Hsuan Wang, Yian Wang, Katerina Fragkiadaki, Zackory Erickson, David Held, Chuang Gan

LLM and Simulation as Bilevel Optimizers: A New Paradigm to Advance Physical Scientific Discovery

Pingchuan Ma, Tsun-Hsuan Wang, Minghao Guo, Zhiqing Sun, Joshua B. Tenenbaum, Daniela Rus, Chuang Gan, Wojciech Matusik

Large Scale Dataset Distillation with Domain Shift

Noel Loo, Alaa Maalouf, Ramin Hasani, Mathias Lechner, Alexander Amini, Daniela Rus

Growing Q-Networks: Solving Continuous Control Tasks with Adaptive Control Resolution

Tim Seyde, Peter Werner, Wilko Schwarting, Markus Wulfmeier, Daniela Rus