Generating Automatic Curricula via Self-Supervised Active Domain Randomization. - Sharath Chandra Raparthy; Bhairav Mehta; Florian Golemo; Liam Paull (CoRR, 2020)

Curriculum in Gradient-Based Meta-Reinforcement Learning. - Bhairav Mehta; Tristan Deleu; Sharath Chandra Raparthy; Christopher J. Pal; Liam Paull (CoRR, 2020)

CARL: Conditional-value-at-risk Adversarial Reinforcement Learning. - Mathieu Godbout; Maxime Heuillet; Sharath Chandra; Rupali Bhati; Audrey Durand (CoRR, 2021)

A Game-Theoretic Perspective on Risk-Sensitive Reinforcement Learning. - Mathieu Godbout; Maxime Heuillet; Sharath Chandra Raparthy; Rupali Bhati; Audrey Durand (SafeAI@AAAI, 2022)

Compositional Attention: Disentangling Search and Retrieval. - Sarthak Mittal; Sharath Chandra Raparthy; Irina Rish; Yoshua Bengio; Guillaume Lajoie (ICLR, 2022)

Continual Learning In Environments With Polynomial Mixing Times. - Matthew Riemer; Sharath Chandra Raparthy; Ignacio Cases; Gopeshh Subbaraj; Maximilian Puelma Touzel; Irina Rish (NeurIPS, 2022)

Multi-Objective GFlowNets. - Moksh Jain; Sharath Chandra Raparthy; Alex Hernández-García; Jarrid Rector-Brooks; Yoshua Bengio; Santiago Miret; Emmanuel Bengio (ICML, 2023)

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 (ICML, 2024)

Generalization to New Sequential Decision Making Tasks with In-Context Learning. - Sharath Chandra Raparthy; Eric Hambro; Robert Kirk; Mikael Henaff; Roberta Raileanu (ICML, 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 (NeurIPS, 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)

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)

Surveying the Effects of Quality, Diversity, and Complexity in Synthetic Data From Large Language Models. - Alex Havrilla; Andrew Dai 001; Laura O'Mahony; Koen Oostermeijer; Vera Zisler; Alon Albalak; Fabrizio Milo; Sharath Chandra Raparthy; Kanishk Gandhi; Baber Abbasi; Duy Phung; Maia Iyer; et al. (CoRR, 2024)