3 papers
cs.LG2026
Simplicial Embeddings Improve Sample Efficiency in Actor-Critic Agents
Johan Obando-Ceron, Walter Mayor, Samuel Lavoie +3
Recent works have proposed accelerating the wall-clock training time of actor-critic methods via the use of large-scale environment parallelization; unfortunately, these can someti…
cs.CV2026
Compositional Discrete Latent Code for High Fidelity, Productive Diffusion Models
Samuel Lavoie, Michael Noukhovitch, Aaron Courville
We argue that diffusion models' success in modeling complex distributions is, for the most part, coming from their input conditioning. This paper investigates the representation us…
cs.CV2025
Modeling Caption Diversity in Contrastive Vision-Language Pretraining
Samuel Lavoie, Polina Kirichenko, Mark Ibrahim +4
There are a thousand ways to caption an image. Contrastive Language Pretraining (CLIP) on the other hand, works by mapping an image and its caption to a single vector -- limiting h…