Sarath Chandar

ORCID

Publication Activity (10 Years)

Years Active: 2015-2024
Publications (10 Years): 124

Top Venues

Publications

Darshan Patil, Janarthanan Rajendran, Glen Berseth, Sarath Chandar
Intelligent Switching for Reset-Free RL. ICLR (2024)
Mohammad Reza Samsami, Artem Zholus, Janarthanan Rajendran, Sarath Chandar
Mastering Memory Tasks with World Models. ICLR (2024)
Louis Clouâtre, Amal Zouaq, Sarath Chandar
MVP: Minimal Viable Phrase for Long Text Understanding. LREC/COLING (2024)
Darshan Patil, Janarthanan Rajendran, Glen Berseth, Sarath Chandar
Intelligent Switching for Reset-Free RL. CoRR (2024)
Pranshu Malviya, Gonçalo Mordido, Aristide Baratin, Reza Babanezhad Harikandeh, Jerry Huang, Simon Lacoste-Julien, Razvan Pascanu, Sarath Chandar
Promoting Exploration in Memory-Augmented Adam using Critical Momenta. Trans. Mach. Learn. Res. 2024 (2024)
Andreas Madsen, Sarath Chandar, Siva Reddy
Are self-explanations from Large Language Models faithful? CoRR (2024)
Megh Thakkar, Quentin Fournier, Matthew D. Riemer, Pin-Yu Chen, Amal Zouaq, Payel Das, Sarath Chandar
A Deep Dive into the Trade-Offs of Parameter-Efficient Preference Alignment Techniques. CoRR (2024)
Andreas Madsen, Himabindu Lakkaraju, Siva Reddy, Sarath Chandar
Interpretability Needs a New Paradigm. CoRR (2024)
Pranshu Malviya, Jerry Huang, Quentin Fournier, Sarath Chandar
Predicting the Impact of Model Expansion through the Minima Manifold: A Loss Landscape Perspective. CoRR (2024)
Abdelrahman Zayed, Gonçalo Mordido, Ioana Baldini, Sarath Chandar
Why Don't Prompt-Based Fairness Metrics Correlate? ACL (1) (2024)
Abdelrahman Zayed, Gonçalo Mordido, Ioana Baldini, Sarath Chandar
Why Don't Prompt-Based Fairness Metrics Correlate? CoRR (2024)
Jerry Huang, Prasanna Parthasarathi, Mehdi Rezagholizadeh, Sarath Chandar
Towards Practical Tool Usage for Continually Learning LLMs. CoRR (2024)
Doriane Olewicki, Sarra Habchi, Mathieu Nayrolles, Mojtaba Faramarzi, Sarath Chandar, Bram Adams
On the Costs and Benefits of Adopting Lifelong Learning for Software Analytics - Empirical Study on Brown Build and Risk Prediction. ICSE-SEIP (2024)
Artem Zholus, Maksim Kuznetsov, Roman Schutski, Rim Shayakhmetov, Daniil Polykovskiy, Sarath Chandar, Alex Zhavoronkov
BindGPT: A Scalable Framework for 3D Molecular Design via Language Modeling and Reinforcement Learning. CoRR (2024)
Maryam Hashemzadeh, Elias Stengel-Eskin, Sarath Chandar, Marc-Alexandre Côté
Sub-goal Distillation: A Method to Improve Small Language Agents. CoRR (2024)
Mohammad Reza Samsami, Artem Zholus, Janarthanan Rajendran, Sarath Chandar
Mastering Memory Tasks with World Models. CoRR (2024)
Megh Thakkar, Quentin Fournier, Matthew Riemer, Pin-Yu Chen, Amal Zouaq, Payel Das, Sarath Chandar
A Deep Dive into the Trade-Offs of Parameter-Efficient Preference Alignment Techniques. ACL (1) (2024)
Andreas Madsen, Sarath Chandar, Siva Reddy
Are self-explanations from Large Language Models faithful? ACL (Findings) (2024)
Abdelrahman Zayed, Gonçalo Mordido, Samira Shabanian, Ioana Baldini, Sarath Chandar
Fairness-Aware Structured Pruning in Transformers. AAAI (2024)
Kamran Chitsaz, Quentin Fournier, Gonçalo Mordido, Sarath Chandar
Exploring Quantization for Efficient Pre-Training of Transformer Language Models. CoRR (2024)
Abdelrahman Zayed, Gonçalo Mordido, Samira Shabanian, Ioana Baldini, Sarath Chandar
Fairness-Aware Structured Pruning in Transformers. CoRR (2023)
Sanket Vaibhav Mehta, Darshan Patil, Sarath Chandar, Emma Strubell
An Empirical Investigation of the Role of Pre-training in Lifelong Learning. J. Mach. Learn. Res. 24 (2023)
Andreas Madsen, Siva Reddy, Sarath Chandar
Faithfulness Measurable Masked Language Models. CoRR (2023)
Gabriele Prato, Jerry Huang, Prasanna Parthasarathi, Shagun Sodhani, Sarath Chandar
EpiK-Eval: Evaluation for Language Models as Epistemic Models. EMNLP (2023)
Ali Rahimi-Kalahroudi, Janarthanan Rajendran, Ida Momennejad, Harm van Seijen, Sarath Chandar
Replay Buffer with Local Forgetting for Adapting to Local Environment Changes in Deep Model-Based Reinforcement Learning. CoLLAs (2023)
Xutong Zhao, Yangchen Pan, Chenjun Xiao, Sarath Chandar, Janarthanan Rajendran
Conditionally optimistic exploration for cooperative deep multi-agent reinforcement learning. UAI (2023)
Doriane Olewicki, Sarra Habchi, Mathieu Nayrolles, Mojtaba Faramarzi, Sarath Chandar, Bram Adams
Towards Lifelong Learning for Software Analytics Models: Empirical Study on Brown Build and Risk Prediction. CoRR (2023)
Ali Rahimi-Kalahroudi, Janarthanan Rajendran, Ida Momennejad, Harm van Seijen, Sarath Chandar
Replay Buffer With Local Forgetting for Adaptive Deep Model-Based Reinforcement Learning. CoRR (2023)
Abdelrahman Zayed, Prasanna Parthasarathi, Gonçalo Mordido, Hamid Palangi, Samira Shabanian, Sarath Chandar
Deep Learning on a Healthy Data Diet: Finding Important Examples for Fairness. AAAI (2023)
Megh Thakkar, Tolga Bolukbasi, Sriram Ganapathy, Shikhar Vashishth, Sarath Chandar, Partha Talukdar
Self-Influence Guided Data Reweighting for Language Model Pre-training. CoRR (2023)
Abdelrahman Zayed, Gonçalo Mordido, Samira Shabanian, Sarath Chandar
Should We Attend More or Less? Modulating Attention for Fairness. CoRR (2023)
Hadi Nekoei, Xutong Zhao, Janarthanan Rajendran, Miao Liu, Sarath Chandar
Towards Few-shot Coordination: Revisiting Ad-hoc Teamplay Challenge In the Game of Hanabi. CoRR (2023)
Amirhossein Kazemnejad, Mehdi Rezagholizadeh, Prasanna Parthasarathi, Sarath Chandar
Measuring the Knowledge Acquisition-Utilization Gap in Pretrained Language Models. EMNLP (Findings) (2023)
Pranshu Malviya, Gonçalo Mordido, Aristide Baratin, Reza Babanezhad Harikandeh, Jerry Huang, Simon Lacoste-Julien, Razvan Pascanu, Sarath Chandar
Promoting Exploration in Memory-Augmented Adam using Critical Momenta. CoRR (2023)
Xutong Zhao, Yangchen Pan, Chenjun Xiao, Sarath Chandar, Janarthanan Rajendran
Conditionally Optimistic Exploration for Cooperative Deep Multi-Agent Reinforcement Learning. CoRR (2023)
Amirhossein Kazemnejad, Mehdi Rezagholizadeh, Prasanna Parthasarathi, Sarath Chandar
Measuring the Knowledge Acquisition-Utilization Gap in Pretrained Language Models. CoRR (2023)
Hadi Nekoei, Akilesh Badrinaaraayanan, Amit Sinha, Mohammad Amini, Janarthanan Rajendran, Aditya Mahajan, Sarath Chandar
Dealing With Non-stationarity in Decentralized Cooperative Multi-Agent Deep Reinforcement Learning via Multi-Timescale Learning. CoRR (2023)
Hadi Nekoei, Xutong Zhao, Janarthanan Rajendran, Miao Liu, Sarath Chandar
Towards Few-shot Coordination: Revisiting Ad-hoc Teamplay Challenge In the Game of Hanabi. CoLLAs (2023)
Arjun Vaithilingam Sudhakar, Prasanna Parthasarathi, Janarthanan Rajendran, Sarath Chandar
Language Model-In-The-Loop: Data Optimal Approach to Learn-To-Recommend Actions in Text Games. CoRR (2023)
Gabriele Prato, Jerry Huang, Prasanna Parthasarathi, Shagun Sodhani, Sarath Chandar
EpiK-Eval: Evaluation for Language Models as Epistemic Models. CoRR (2023)
Andreas Madsen, Siva Reddy, Sarath Chandar
Post-hoc Interpretability for Neural NLP: A Survey. ACM Comput. Surv. 55 (8) (2023)
Jarrid Rector-Brooks, Kanika Madan, Moksh Jain, Maksym Korablyov, Cheng-Hao Liu, Sarath Chandar, Nikolay Malkin, Yoshua Bengio
Thompson sampling for improved exploration in GFlowNets. CoRR (2023)
Hadi Nekoei, Akilesh Badrinaaraayanan, Amit Sinha, Mohammad Amini, Janarthanan Rajendran, Aditya Mahajan, Sarath Chandar
Dealing With Non-stationarity in Decentralized Cooperative Multi-Agent Deep Reinforcement Learning via Multi-Timescale Learning. CoLLAs (2023)
Megh Thakkar, Tolga Bolukbasi, Sriram Ganapathy, Shikhar Vashishth, Sarath Chandar, Partha Talukdar
Self-Influence Guided Data Reweighting for Language Model Pre-training. EMNLP (2023)
Gonçalo Mordido, Pranshu Malviya, Aristide Baratin, Sarath Chandar
Lookbehind Optimizer: k steps back, 1 step forward. CoRR (2023)
Louis Clouâtre, Prasanna Parthasarathi, Amal Zouaq, Sarath Chandar
Detecting Languages Unintelligible to Multilingual Models through Local Structure Probes. CoRR (2022)
Simon Guiroy, Christopher Pal, Gonçalo Mordido, Sarath Chandar
Improving Meta-Learning Generalization with Activation-Based Early-Stopping. CoRR (2022)
Louis Clouâtre, Prasanna Parthasarathi, Amal Zouaq, Sarath Chandar
Local Structure Matters Most: Perturbation Study in NLU. ACL (Findings) (2022)
Simon Guiroy, Christopher Pal, Gonçalo Mordido, Sarath Chandar
Improving Meta-Learning Generalization with Activation-Based Early-Stopping. CoLLAs (2022)
Mojtaba Faramarzi, Mohammad Amini, Akilesh Badrinaaraayanan, Vikas Verma, Sarath Chandar
PatchUp: A Feature-Space Block-Level Regularization Technique for Convolutional Neural Networks. AAAI (2022)
Amir Ardalan Kalantari, Mohammad Amini, Sarath Chandar, Doina Precup
Improving Sample Efficiency of Value Based Models Using Attention and Vision Transformers. CoRR (2022)
Paul-Aymeric Martin McRae, Prasanna Parthasarathi, Mido Assran, Sarath Chandar
Memory Augmented Optimizers for Deep Learning. ICLR (2022)
Gabriele Prato, Yale Song, Janarthanan Rajendran, R. Devon Hjelm, Neel Joshi, Sarath Chandar
PatchBlender: A Motion Prior for Video Transformers. CoRR (2022)
Louis Clouâtre, Prasanna Parthasarathi, Amal Zouaq, Sarath Chandar
Local Structure Matters Most in Most Languages. CoRR (2022)
Enamundram Naga Karthik, Anne Kerbrat, Pierre Labauge, Tobias Granberg, Jason Talbott, Daniel S. Reich, Massimo Filippi, Rohit Bakshi, Virginie Callot, Sarath Chandar, Julien Cohen-Adad
Segmentation of Multiple Sclerosis Lesions across Hospitals: Learn Continually or Train from Scratch? CoRR (2022)
Shagun Sodhani, Mojtaba Faramarzi, Sanket Vaibhav Mehta, Pranshu Malviya, Mohamed Abdelsalam, Janarthanan Rajendran, Sarath Chandar
An Introduction to Lifelong Supervised Learning. CoRR (2022)
Daphné Lafleur, Sarath Chandar, Gilles Pesant
Combining Reinforcement Learning and Constraint Programming for Sequence-Generation Tasks with Hard Constraints. CP (2022)
Yi Wan, Ali Rahimi-Kalahroudi, Janarthanan Rajendran, Ida Momennejad, Sarath Chandar, Harm van Seijen
Towards Evaluating Adaptivity of Model-Based Reinforcement Learning Methods. ICML (2022)
Abdelrahman Zayed, Prasanna Parthasarathi, Gonçalo Mordido, Hamid Palangi, Samira Shabanian, Sarath Chandar
Deep Learning on a Healthy Data Diet: Finding Important Examples for Fairness. CoRR (2022)
Louis Clouâtre, Prasanna Parthasarathi, Amal Zouaq, Sarath Chandar
Detecting Languages Unintelligible to Multilingual Models through Local Structure Probes. EMNLP (Findings) (2022)
Yi Wan, Ali Rahimi-Kalahroudi, Janarthanan Rajendran, Ida Momennejad, Sarath Chandar, Harm van Seijen
Towards Evaluating Adaptivity of Model-Based Reinforcement Learning Methods. CoRR (2022)
Pranshu Malviya, Balaraman Ravindran, Sarath Chandar
TAG: Task-based Accumulated Gradients for Lifelong learning. CoLLAs (2022)
Louis Clouâtre, Prasanna Parthasarathi, Amal Zouaq, Sarath Chandar
Local Structure Matters Most in Most Languages. AACL/IJCNLP (2) (2022)
Gonçalo Mordido, Sarath Chandar, François Leduc-Primeau
Sharpness-Aware Training for Accurate Inference on Noisy DNN Accelerators. CoRR (2022)
Gabriele Prato, Simon Guiroy, Ethan Caballero, Irina Rish, Sarath Chandar
Scaling Laws for the Few-Shot Adaptation of Pre-trained Image Classifiers. CoRR (2021)
Paul-Aymeric McRae, Prasanna Parthasarathi, Mahmoud Assran, Sarath Chandar
Memory Augmented Optimizers for Deep Learning. CoRR (2021)
Louis Clouâtre, Prasanna Parthasarathi, Amal Zouaq, Sarath Chandar
Demystifying Neural Language Models' Insensitivity to Word-Order. CoRR (2021)
Prasanna Parthasarathi, Mohamed Abdelsalam, Joelle Pineau, Sarath Chandar
A Brief Study on the Effects of Training Generative Dialogue Models with a Semantic loss. CoRR (2021)
Louis Clouâtre, Philippe Trempe, Amal Zouaq, Sarath Chandar
MLMLM: Link Prediction with Mean Likelihood Masked Language Model. ACL/IJCNLP (Findings) (2021)
Andreas Madsen, Siva Reddy, Sarath Chandar
Post-hoc Interpretability for Neural NLP: A Survey. CoRR (2021)
Pranshu Malviya, Balaraman Ravindran, Sarath Chandar
TAG: Task-based Accumulated Gradients for Lifelong learning. CoRR (2021)
Hadi Nekoei, Akilesh Badrinaaraayanan, Aaron C. Courville, Sarath Chandar
Continuous Coordination As a Realistic Scenario for Lifelong Learning. ICML (2021)
Sai Krishna Gottipati, Yashaswi Pathak, Boris Sattarov, Sahir, Rohan Nuttall, Mohammad Amini, Matthew E. Taylor, Sarath Chandar
Towered Actor Critic For Handling Multiple Action Types In Reinforcement Learning For Drug Discovery. AAAI (2021)
Prasanna Parthasarathi, Joelle Pineau, Sarath Chandar
Do Encoder Representations of Generative Dialogue Models Encode Sufficient Information about the Task ? CoRR (2021)
Mohamed Abdelsalam, Mojtaba Faramarzi, Shagun Sodhani, Sarath Chandar
IIRC: Incremental Implicitly-Refined Classification. CVPR (2021)
Prasanna Parthasarathi, Joelle Pineau, Sarath Chandar
Do Encoder Representations of Generative Dialogue Models have sufficient summary of the Information about the task ? SIGDIAL (2021)
Sanket Vaibhav Mehta, Darshan Patil, Sarath Chandar, Emma Strubell
An Empirical Investigation of the Role of Pre-training in Lifelong Learning. CoRR (2021)
Steven Y. Feng, Varun Gangal, Jason Wei, Sarath Chandar, Soroush Vosoughi, Teruko Mitamura, Eduard H. Hovy
A Survey of Data Augmentation Approaches for NLP. ACL/IJCNLP (Findings) (2021)
Hadi Nekoei, Akilesh Badrinaaraayanan, Aaron C. Courville, Sarath Chandar
Continuous Coordination As a Realistic Scenario for Lifelong Learning. CoRR (2021)
Prasanna Parthasarathi, Mohamed Abdelsalam, Sarath Chandar, Joelle Pineau
A Brief Study on the Effects of Training Generative Dialogue Models with a Semantic loss. SIGDIAL (2021)
Steven Y. Feng, Varun Gangal, Jason Wei, Sarath Chandar, Soroush Vosoughi, Teruko Mitamura, Eduard H. Hovy
A Survey of Data Augmentation Approaches for NLP. CoRR (2021)
Sai Krishna Gottipati, Boris Sattarov, Sufeng Niu, Yashaswi Pathak, Haoran Wei, Shengchao Liu, Simon Blackburn, Karam M. J. Thomas, Connor W. Coley, Jian Tang, Sarath Chandar, Yoshua Bengio
Learning to Navigate The Synthetically Accessible Chemical Space Using Reinforcement Learning. ICML (2020)
Harm van Seijen, Hadi Nekoei, Evan Racah, Sarath Chandar
The LoCA Regret: A Consistent Metric to Evaluate Model-Based Behavior in Reinforcement Learning. CoRR (2020)
Mohamed Abdelsalam, Mojtaba Faramarzi, Shagun Sodhani, Sarath Chandar
IIRC: Incremental Implicitly-Refined Classification. CoRR (2020)
Harm van Seijen, Hadi Nekoei, Evan Racah, Sarath Chandar
The LoCA Regret: A Consistent Metric to Evaluate Model-Based Behavior in Reinforcement Learning. NeurIPS (2020)
Sai Krishna Gottipati, Boris Sattarov, Sufeng Niu, Yashaswi Pathak, Haoran Wei, Shengchao Liu, Karam M. J. Thomas, Simon Blackburn, Connor W. Coley, Jian Tang, Sarath Chandar, Yoshua Bengio
Learning To Navigate The Synthetically Accessible Chemical Space Using Reinforcement Learning. CoRR (2020)
Evan Racah, Sarath Chandar
Slot Contrastive Networks: A Contrastive Approach for Representing Objects. CoRR (2020)
Nolan Bard, Jakob N. Foerster, Sarath Chandar, Neil Burch, Marc Lanctot, H. Francis Song, Emilio Parisotto, Vincent Dumoulin, Subhodeep Moitra, Edward Hughes, Iain Dunning, Shibl Mourad, Hugo Larochelle, Marc G. Bellemare, Michael Bowling
The Hanabi challenge: A new frontier for AI research. Artif. Intell. 280 (2020)
Prasanna Parthasarathi, Joelle Pineau, Sarath Chandar
How To Evaluate Your Dialogue System: Probe Tasks as an Alternative for Token-level Evaluation Metrics. CoRR (2020)
Louis Clouâtre, Philippe Trempe, Amal Zouaq, Sarath Chandar
MLMLM: Link Prediction with Mean Likelihood Masked Language Model. CoRR (2020)
Sai Krishna Gottipati, Yashaswi Pathak, Rohan Nuttall, Sahir, Raviteja Chunduru, Ahmed Touati, Sriram Ganapathi Subramanian, Matthew E. Taylor, Sarath Chandar
Maximum Reward Formulation In Reinforcement Learning. CoRR (2020)
Shagun Sodhani, Sarath Chandar, Yoshua Bengio
Toward Training Recurrent Neural Networks for Lifelong Learning. Neural Comput. 32 (1) (2020)
Mojtaba Faramarzi, Mohammad Amini, Akilesh Badrinaaraayanan, Vikas Verma, Sarath Chandar
PatchUp: A Regularization Technique for Convolutional Neural Networks. CoRR (2020)
Nolan Bard, Jakob N. Foerster, Sarath Chandar, Neil Burch, Marc Lanctot, H. Francis Song, Emilio Parisotto, Vincent Dumoulin, Subhodeep Moitra, Edward Hughes, Iain Dunning, Shibl Mourad, Hugo Larochelle, Marc G. Bellemare, Michael Bowling
The Hanabi Challenge: A New Frontier for AI Research. CoRR (2019)
Vardaan Pahuja, Jie Fu, Sarath Chandar, Christopher J. Pal
Structure Learning for Neural Module Networks. CoRR (2019)
Sarath Chandar, Chinnadhurai Sankar, Eugene Vorontsov, Samira Ebrahimi Kahou, Yoshua Bengio
Towards Non-Saturating Recurrent Units for Modelling Long-Term Dependencies. AAAI (2019)
Sarath Chandar, Chinnadhurai Sankar, Eugene Vorontsov, Samira Ebrahimi Kahou, Yoshua Bengio
Towards Non-saturating Recurrent Units for Modelling Long-term Dependencies. CoRR (2019)
Revanth Reddy, Sarath Chandar, Balaraman Ravindran
Edge Replacement Grammars: A Formal Language Approach for Generating Graphs. CoRR (2019)
Chinnadhurai Sankar, Sandeep Subramanian, Chris Pal, Sarath Chandar, Yoshua Bengio
Do Neural Dialog Systems Use the Conversation History Effectively? An Empirical Study. ACL (1) (2019)
Chinnadhurai Sankar, Sandeep Subramanian, Christopher J. Pal, Sarath Chandar, Yoshua Bengio
Do Neural Dialog Systems Use the Conversation History Effectively? An Empirical Study. CoRR (2019)

Sarath Chandar.css-eqlu8i{font-size:small;padding-left:4px;}

Publication Activity (10 Years)

Top Topics

Top Venues

Sarath Chandar