Sharath Chandra

According to our database, Sharath Chandra authored at least 13 papers between 2020 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Surveying the Effects of Quality, Diversity, and Complexity in Synthetic Data From Large Language Models.

Alex Havrilla, Andrew Dai, Laura O'Mahony, Koen Oostermeijer, Vera Zisler, Alon Albalak, Fabrizio Milo, Sharath Chandra Raparthy, Kanishk Gandhi, Baber Abbasi, Duy Phung, Maia Iyer, Dakota Mahan, Chase Blagden, Srishti Gureja, Mohammed Hamdy, Wen-Ding Li, Giovanni Paolini, Pawan Sasanka Ammanamanchi, Elliot Meyerson

CoRR, 2024

Teaching Large Language Models to Reason with Reinforcement Learning.

Alex Havrilla, Yuqing Du, Sharath Chandra Raparthy, Christoforos Nalmpantis, Jane Dwivedi-Yu, Maksym Zhuravinskyi, Eric Hambro, Sainbayar Sukhbaatar, Roberta Raileanu

CoRR, 2024

GLoRe: When, Where, and How to Improve LLM Reasoning via Global and Local Refinements.

Alex Havrilla, Sharath Chandra Raparthy, Christoforos Nalmpantis, Jane Dwivedi-Yu, Maksym Zhuravinskyi, Eric Hambro, Roberta Railneau

CoRR, 2024

Rainbow Teaming: Open-Ended Generation of Diverse Adversarial Prompts.

Mikayel Samvelyan, Sharath Chandra Raparthy, Andrei Lupu, Eric Hambro, Aram H. Markosyan, Manish Bhatt, Yuning Mao, Minqi Jiang, Jack Parker-Holder, Jakob N. Foerster, Tim Rocktäschel, Roberta Raileanu

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

Generalization to New Sequential Decision Making Tasks with In-Context Learning.

Sharath Chandra Raparthy, Eric Hambro, Robert Kirk, Mikael Henaff, Roberta Raileanu

Proceedings of the Forty-first International Conference on Machine Learning, 2024

GLoRe: When, Where, and How to Improve LLM Reasoning via Global and Local Refinements.

Alexander Havrilla, Sharath Chandra Raparthy, Christoforos Nalmpantis, Jane Dwivedi-Yu, Maksym Zhuravinskyi, Eric Hambro, Roberta Raileanu

Proceedings of the Forty-first International Conference on Machine Learning, 2024

2023

Multi-Objective GFlowNets.

Moksh Jain, Sharath Chandra Raparthy, Alex Hernández-García, Jarrid Rector-Brooks, Yoshua Bengio, Santiago Miret, Emmanuel Bengio

Proceedings of the International Conference on Machine Learning, 2023

2022

Continual Learning In Environments With Polynomial Mixing Times.

Matthew Riemer, Sharath Chandra Raparthy, Ignacio Cases, Gopeshh Subbaraj, Maximilian Puelma Touzel, Irina Rish

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Compositional Attention: Disentangling Search and Retrieval.

Sarthak Mittal, Sharath Chandra Raparthy, Irina Rish, Yoshua Bengio, Guillaume Lajoie

Proceedings of the Tenth International Conference on Learning Representations, 2022

A Game-Theoretic Perspective on Risk-Sensitive Reinforcement Learning.

Mathieu Godbout, Maxime Heuillet, Sharath Chandra Raparthy, Rupali Bhati, Audrey Durand

Proceedings of the Workshop on Artificial Intelligence Safety 2022 (SafeAI 2022) co-located with the Thirty-Sixth AAAI Conference on Artificial Intelligence (AAAI2022), 2022

2021

CARL: Conditional-value-at-risk Adversarial Reinforcement Learning.

Mathieu Godbout, Maxime Heuillet, Sharath Chandra, Rupali Bhati, Audrey Durand

CoRR, 2021

2020

Curriculum in Gradient-Based Meta-Reinforcement Learning.

Bhairav Mehta, Tristan Deleu, Sharath Chandra Raparthy, Christopher J. Pal, Liam Paull

CoRR, 2020

Generating Automatic Curricula via Self-Supervised Active Domain Randomization.

Sharath Chandra Raparthy, Bhairav Mehta, Florian Golemo, Liam Paull

CoRR, 2020