4 papers
Assessing Factual Music Comprehension in Large Audio Language Models
Daniel Chenyu Lin, Michael Freeman, John Thickstun
Large audio language models (LALMs) leverage multimodal representations to generate open-ended answers to natural language queries about audio. In this paper, we (1) provide empiri…
Goal Force: Teaching Video Models To Accomplish Physics-Conditioned Goals
Nate Gillman, Yinghua Zhou, Zitian Tang +6
Recent advancements in video generation have enabled the development of ``world models'' capable of simulating potential futures for robotics and planning. However, specifying prec…
Force Prompting: Video Generation Models Can Learn and Generalize Physics-based Control Signals
Nate Gillman, Charles Herrmann, Michael Freeman +4
Recent advances in video generation models have sparked interest in world models capable of simulating realistic environments. While navigation has been well-explored, physically m…
Fourier Head: Helping Large Language Models Learn Complex Probability Distributions
Nate Gillman, Daksh Aggarwal, Michael Freeman +2
As the quality of large language models has improved, there has been increased interest in using them to model non-linguistic tokens. For example, the Decision Transformer recasts…