Publications

Preprints

• Unraveling the Complexity of Memory in RL Agents: An Approach for Classification and Evaluation
  Egor Cherepanov, Nikita Kachaev, Artem Zholus, Alexey K. Kovalev, and Aleksandr I. Panov
  In ArXiv, 2024.
  #RL
  [arXiv]

• ChartGemma: Visual Instruction-tuning for Chart Reasoning in the Wild
  Ahmed Masry*, Megh Thakkar*, Aayush Bajaj, Aaryaman Kartha, Enamul Hoque, and Shafiq Joty
  In arXiv, 2024.
  #NLP
  [arXiv], [code]

• 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]

• Exploring the Plasticity of Neural Network for NLP Tasks in Continual Learning
  Maryam Hashemzadeh, Pranshu Malviya*, Darshan Patil*, and Sarath Chandar
  Conference on Lifelong Learning Agents (CoLLAs) Workshop Track, 2024.
  #DL, #NLP
  

• 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
  In ArXiv, 2024.
  #Other
  [arXiv]

• IDAT: A Multi-Modal Dataset and Toolkit for Building and Evaluating Interactive Task-Solving Agents
  Shrestha Mohanty, Negar Arabzadeh, Andrea Tupini, Yuxuan Sun, Alexey Skrynnik, Artem Zholus, Marc-Alexandre Côté, and Julia Kiseleva
  In ArXiv, 2024.
  #NLP
  [arXiv]

• Predicting the Impact of Model Expansion through the Minima Manifold: A Loss Landscape Perspective
  Pranshu Malviya, Jerry Huang, Quentin Fournier, and Sarath Chandar
  In ArXiv, 2024.
  #DL
  [arXiv]

• Interpretability Needs a New Paradigm
  Andreas Madsen, Himabindu Lakkaraju, Siva Reddy, and Sarath Chandar
  In ArXiv, 2024.
  #NLP, #DL, #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.
  #DL
  [arXiv], [code]

• Feature diversity in self-supervised learning
  Pranshu Malviya* and Arjun Vaithilingam Sudhakar*
  Conference on Lifelong Learning Agents (CoLLAs) Workshop Track, 2022.
  #DL
  [arXiv]

• Sharpness-Aware Training for Accurate Inference on Noisy DNN Accelerators
  Gonçalo Mordido, Sarath Chandar, and François Leduc-Primeau
  Conference on Lifelong Learning Agents (CoLLAs) Workshop Track, 2022.
  [Edge Intelligence Workshop (EIW), 2022]
  #DL
  [arXiv]

• An Introduction to Lifelong Supervised Learning
  Shagun Sodhani, Mojtaba Farmazi, Sanket Vaibhav Mehta, Pranshu Malviya, Mohamed Abdelsalam, Janarthanan Rajendran, and Sarath Chandar
  In ArXiv, 2022.
  #DL
  [arXiv]

• Maximum Reward Formulation In Reinforcement Learning
  Sai Krishna Gottipati, Yashaswi Pathak, Rohan Nuttall, Raviteja Chunduru, Ahmed Touati, Sriram Ganapathi Subramanian, Matthew E Taylor, and Sarath Chandar
  In arXiv, 2020.
  #RL
  [arXiv]