Sotabase

Career

· Honorary Lecturer (Adjunct Professor), UCL2023–
· Research Scientist Intern, DeepMind2021–2021
· Research Scientist Intern, Google DeepMind2021–2021
· Research Scientist, Meta2021–
· Research Intern, Facebook AI2019–2019
· Research Intern, Microsoft2018–2018
· Research Intern, Facebook AI2017–2019
· PhD Student, NYU Graduate School of Arts and Science2016–2021
· Undergraduate Researcher, Princeton University2015–2016
· Research Internship, ETH Zurich2014–2014
· Permanent Board Member For Princeton University Physics Competition, Princeton University2014–2015
· Undergraduate Researcher, Princeton University2014–2016
· Research Internship, Max Planck Institute for Extraterrestrial Physics2013–2013
· Co-president Of Astrobiology Club, Princeton University2013–2015
· Bachelor’s Degree, Astrophysics, Princeton University2012–2016
· Student, Princeton University2012–2016

Publications (82)

The Llama 3 Herd of Models
2024
12,282
cited
Toolformer: Language Models Can Teach Themselves to Use Tools
Neural Information Processing Systems · 2023
2,831
cited
Augmented Language Models: a Survey
Trans. Mach. Learn. Res. · 2023
499
cited
Challenges and Applications of Large Language Models
arXiv.org · 2023
446
cited
Chain-of-Verification Reduces Hallucination in Large Language Models
Annual Meeting of the Association for Computational Linguistics · 2023
345
cited
Understanding the Effects of RLHF on LLM Generalisation and Diversity
International Conference on Learning Representations · 2023
281
cited
Modeling Others using Oneself in Multi-Agent Reinforcement Learning
International Conference on Machine Learning · 2018
221
cited
Open-Ended Learning Leads to Generally Capable Agents
arXiv.org · 2021
220
cited
The NetHack Learning Environment
Neural Information Processing Systems · 2020
210
cited
RIDE: Rewarding Impact-Driven Exploration for Procedurally-Generated Environments
International Conference on Learning Representations · 2020
194
cited
Rainbow Teaming: Open-Ended Generation of Diverse Adversarial Prompts
Neural Information Processing Systems · 2024
158
cited
Teaching Large Language Models to Reason with Reinforcement Learning
arXiv.org · 2024
148
cited
Learning with AMIGo: Adversarially Motivated Intrinsic Goals
International Conference on Learning Representations · 2020
140
cited
Automatic Data Augmentation for Generalization in Reinforcement Learning
Neural Information Processing Systems · 2021
128
cited
SUPERBUBBLES IN THE MULTIPHASE ISM AND THE LOADING OF GALACTIC WINDS
2016
118
cited
Automatic Data Augmentation for Generalization in Deep Reinforcement Learning
arXiv.org · 2020
115
cited
Decoupling Value and Policy for Generalization in Reinforcement Learning
International Conference on Machine Learning · 2021
112
cited
Motif: Intrinsic Motivation from Artificial Intelligence Feedback
International Conference on Learning Representations · 2023
90
cited
Hyperparameters in Reinforcement Learning and How To Tune Them
International Conference on Machine Learning · 2023
74
cited
Improving Intrinsic Exploration with Language Abstractions
Neural Information Processing Systems · 2022
73
cited
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