Publications | Miscellaneous

Preprints

• CrystalGym: A New Benchmark for Materials Discovery Using Reinforcement Learning
  Prashant Govindarajan, Mathieu Reymond, Antoine Clavaud, Mariano Phielipp, Santiago Miret, and Sarath Chandar
  In ArXiv, 2025.
  #RL, #Other
  [arXiv]

• NovoMolGen: Rethinking Molecular Language Model Pretraining
  Kamran Chitsaz*, Roshan Balaji*, Quentin Fournier, Nirav Pravinbhai Bhatt, and Sarath Chandar
  In ArXiv, 2025.
  #NLP, #Other
  [arXiv]

• Structure-Aligned Protein Language Model
  Can Chen, David Heurtel-Depeiges, Robert M. Vernon, Christopher James Langmead, Yoshua Bengio, and Quentin Fournier
  In ArXiv, 2025.
  #NLP, #Other
  [arXiv]

• Protein Language Models: Is Scaling Necessary?
  Quentin Fournier, Robert M. Vernon, Almer van der Sloot, Benjamin Schulz, Sarath Chandar, and Christopher James Langmead
  In bioRxiv, 2024.
  #DL, #Other
  [bioRxiv], [code]

• Interpretability in Action: Exploratory Analysis of VPT, a Minecraft Agent
  Karolis Jucys, George Adamopoulos, Mehrab Hamidi, Stephanie Milani, Mohammad Reza Samsami, Artem Zholus, Sonia Joseph, Blake Richards, Irina Rish, and Özgür Şimşek
  Workshop on Mechanistic Interpretability @ ICML, 2024.
  #Other
  [arXiv]

• Segmentation of Multiple Sclerosis Lesions across Hospitals: Learn Continually or Train from Scratch?
  Naga Karthik Enamundram, Anne Kerbrat, Pierre Labauge, Tobias Granberg, Jason Talbott, Daniel S. Reich, Massimo Filippi, Rohit Bakshi, Virginie Callot, Sarath Chandar, and Julien Cohen-Adad
  In ArXiv, 2022.
  [Medical Imaging meets NeurIPS, 2022]
  #DL, #Other
  [arXiv], [code]

Conference and Journal Papers

2025

6. TAPNext: Tracking Any Point (TAP) as Next Token Prediction
   Artem Zholus, Carl Doersch, Yi Yang, Skanda Koppula, Viorica Pătrăucean, Xu Owen He, Ignacio Rocco, Mehdi S. M. Sajjadi, Sarath Chandar, and Ross Goroshin
   International Conference on Computer Vision (ICCV), 2025.
   #DL, #Other
   [website], [arXiv], [code], [huggingface], [YouTube]

7. A Generalist Hanabi Agent
   Arjun Vaithilingam Sudhakar*, Hadi Nekoei*, Mathieu Reymond, Miao Liu, Janarthanan Rajendran, and Sarath Chandar
   International Conference on Learning Representations (ICLR), 2025.
   #RL, #Other
   [website], [openreview], [arXiv], [code]

2024

4. Contrast-agnostic Spinal Cord Segmentation: A Comparative Study of ConvNets and Vision Transformers
   Naga Karthik Enamundram, Sandrine Bedard, Jan Valosek, Sarath Chandar, and Julien Cohen-Adad
   Medical Imaging with Deep Learning (MIDL), 2024.
   #DL, #Other
   [openreview]

5. A Responsible Framework for Applying Artificial Intelligence on Medical Images and Signals at the Point-of-care: the PACS-AI Platform
   Pascal Theriault-Lauzier, Denis Cobin, Olivier Tastet, Elodie Labrecque Langlais, Bahareh Taji, Guson Kang, Aun-Yeong Chong, Derek So, An Tang, Judy Wawira Gichoya, Sarath Chandar, Pierre-Luc Déziel, Julie G Hussin, Samuel Kadoury, and Robert Avram
   Canadian Journal of Cardiology, 2024.
   #DL, #Other
   [paper]

2023

2. Label fusion and training methods for reliable representation of inter-rater uncertainty
   Andreanne Lemay, Charley Gros, Naga Karthik Enamundram, and Julien Cohen-Adad
   The Journal of Machine Learning for Biomedical Imaging (MELBA), 2023.
   #DL, #Other
   [paper]

2021

1. Towered Actor Critic for Handling Multiple Action Types in Reinforcement Learning For Drug Discovery
   Sai Krishna Gottipati, Yashaswi Pathak, Boris Sattarov, Sahir, Rohan Nuttall, Mohammad Amini, Matthew E. Taylor, and Sarath Chandar
   AAAI Conference on Artificial Intelligence (AAAI), 2021.
   #RL, #Other
   [aaai]