Publications

Scenario Dreamer: Vectorized Latent Diffusion for Generating Driving Simulation Environments
Luke Rowe
Roger Girgis
Anthony Gosselin
Liam Paull
Chris Pal
Felix Heide
2025-03-28
ArXiv (prépublication)
arxiv.org
arxiv.org
Conditional Diffusion Models are Medical Image Classifiers that Provide Explainability and Uncertainty for Free
Gian Mario Favero
Parham Saremi
Emily Kaczmarek
Brennan Nichyporuk
Tal Arbel
2025-03-27
MIDL.io/2025/Conference (présentation orale)
doi.org
openreview.net
debug-gym: A Text-Based Environment for Interactive Debugging
Xingdi Yuan
Morgane M Moss
Charbel Feghali
Chinmay Singh
Darya Moldavskaya
Drew MacPhee
Lucas Caccia
Matheus Pereira
Minseon Kim
Alessandro Sordoni
Marc-Alexandre Côté
2025-03-27
ArXiv (prépublication)
doi.org
arxiv.org
debug-gym: A Text-Based Environment for Interactive Debugging
Xingdi Yuan
Morgane M Moss
Charbel Feghali
Chinmay Singh
Darya Moldavskaya
Drew MacPhee
Lucas Caccia
Matheus Pereira
Minseon Kim
Alessandro Sordoni
Marc-Alexandre Côté
2025-03-27
ArXiv (prépublication)
arxiv.org
arxiv.org
How do language models learn facts? Dynamics, curricula and hallucinations
Nicolas Zucchet
Jorg Bornschein
Stephanie Chan
Andrew Lampinen
Razvan Pascanu
Soham De
2025-03-27
ArXiv (prépublication)
doi.org
arxiv.org
How do language models learn facts? Dynamics, curricula and hallucinations
Nicolas Zucchet
Jorg Bornschein
Stephanie Chan
Andrew Lampinen
Razvan Pascanu
Soham De
2025-03-27
ArXiv (prépublication)
arxiv.org
arxiv.org
PRISM: High-Resolution&Precise Counterfactual Medical Image Generation using Language-guided Stable Diffusion
Amar Kumar
Anita Kriz
Mohammad Havaei
Tal Arbel
Developing reliable and generalizable deep learning systems for medical imaging faces significant obstacles due to spurious correlations, da… (voir plus)ta imbalances, and limited text annotations in datasets. Addressing these challenges requires architectures robust to the unique complexities posed by medical imaging data. The rapid advancements in vision-language foundation models within the natural image domain prompt the question of how they can be adapted for medical imaging tasks. In this work, we present PRISM, a framework that leverages foundation models to generate high-resolution, language-guided medical image counterfactuals using Stable Diffusion. Our approach demonstrates unprecedented precision in selectively modifying spurious correlations (the medical devices) and disease features, enabling the removal and addition of specific attributes while preserving other image characteristics. Through extensive evaluation, we show how PRISM advances counterfactual generation and enables the development of more robust downstream classifiers for clinically deployable solutions. To facilitate broader adoption and research, we make our code publicly available at https://github.com/Amarkr1/PRISM.
2025-03-27
MIDL.io/2025/Conference (présentation orale)
doi.org
openreview.net
StarFlow: Generating Structured Workflow Outputs From Sketch Images
Patrice Bechard
Chao Wang
Amirhossein Abaskohi
Juan A. Rodriguez
Chris Pal
David Vazquez
Spandana Gella
Sai Rajeswar
Perouz Taslakian
2025-03-27
ArXiv (prépublication)
arxiv.org
arxiv.org
StarFlow: Generating Structured Workflow Outputs From Sketch Images
Patrice Bechard
Chao Wang
Amirhossein Abaskohi
Juan A. Rodriguez
Chris Pal
David Vazquez
Spandana Gella
Sai Rajeswar
Perouz Taslakian
2025-03-27
ArXiv (prépublication)
doi.org
arxiv.org
A Text-guided Protein Design Framework
Shengchao Liu
Yutao Zhu
Yanjing Li
Zhuoxinran Li
Jiarui Lu
Zhao Xu
Weili Nie
Anthony Gitter
Chaowei Xiao
Jian Tang
Arvind Ramanathan
Hongyu Guo
Animashree Anandkumar
2025-03-27
Nature Machine Intelligence (publié)
doi.org
arxiv.org
Assessing SAM for Tree Crown Instance Segmentation from Drone Imagery
Mélisande Teng
Arthur Ouaknine
Etienne Lalibert'e
Yoshua Bengio
David Rolnick
Hugo Larochelle
2025-03-26
ArXiv (prépublication)
doi.org
arxiv.org
Assessing SAM for Tree Crown Instance Segmentation from Drone Imagery
Mélisande Teng
Arthur Ouaknine
Etienne Lalibert'e
Yoshua Bengio
David Rolnick
Hugo Larochelle
2025-03-26
ArXiv (prépublication)
arxiv.org
arxiv.org