Roberta Raileanu

According to our database1, Roberta Raileanu authored at least 35 papers between 2018 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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In proceedings 
Article 
PhD thesis 
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Links

On csauthors.net:

Bibliography

2024
Teaching Large Language Models to Reason with Reinforcement Learning.
CoRR, 2024

Rainbow Teaming: Open-Ended Generation of Diverse Adversarial Prompts.
CoRR, 2024

TOOLVERIFIER: Generalization to New Tools via Self-Verification.
CoRR, 2024

2023
The Generalization Gap in Offline Reinforcement Learning.
CoRR, 2023

Generalization to New Sequential Decision Making Tasks with In-Context Learning.
CoRR, 2023

Understanding the Effects of RLHF on LLM Generalisation and Diversity.
CoRR, 2023

Motif: Intrinsic Motivation from Artificial Intelligence Feedback.
CoRR, 2023

Chain-of-Verification Reduces Hallucination in Large Language Models.
CoRR, 2023

Challenges and Applications of Large Language Models.
CoRR, 2023

Improving Language Plasticity via Pretraining with Active Forgetting.
CoRR, 2023

Augmented Language Models: a Survey.
CoRR, 2023

Toolformer: Language Models Can Teach Themselves to Use Tools.
CoRR, 2023

Toolformer: Language Models Can Teach Themselves to Use Tools.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

On the Importance of Exploration for Generalization in Reinforcement Learning.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Improving Language Plasticity via Pretraining with Active Forgetting.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

A Study of Global and Episodic Bonuses for Exploration in Contextual MDPs.
Proceedings of the International Conference on Machine Learning, 2023

Hyperparameters in Reinforcement Learning and How To Tune Them.
Proceedings of the International Conference on Machine Learning, 2023

MAESTRO: Open-Ended Environment Design for Multi-Agent Reinforcement Learning.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

Building a Subspace of Policies for Scalable Continual Learning.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022
Improving Intrinsic Exploration with Language Abstractions.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Exploration via Elliptical Episodic Bonuses.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Dungeons and Data: A Large-Scale NetHack Dataset.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

2021
Towards More General and Adaptive Deep Reinforcement Learning Agents.
PhD thesis, 2021

Open-Ended Learning Leads to Generally Capable Agents.
CoRR, 2021

Automatic Data Augmentation for Generalization in Reinforcement Learning.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021


Decoupling Value and Policy for Generalization in Reinforcement Learning.
Proceedings of the 38th International Conference on Machine Learning, 2021

Learning with AMIGo: Adversarially Motivated Intrinsic Goals.
Proceedings of the 9th International Conference on Learning Representations, 2021

2020
Fast Adaptation via Policy-Dynamics Value Functions.
CoRR, 2020

Automatic Data Augmentation for Generalization in Deep Reinforcement Learning.
CoRR, 2020

The NetHack Learning Environment.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Fast Adaptation to New Environments via Policy-Dynamics Value Functions.
Proceedings of the 37th International Conference on Machine Learning, 2020

RIDE: Rewarding Impact-Driven Exploration for Procedurally-Generated Environments.
Proceedings of the 8th International Conference on Learning Representations, 2020

2018
Backplay: "Man muss immer umkehren".
CoRR, 2018

Modeling Others using Oneself in Multi-Agent Reinforcement Learning.
Proceedings of the 35th International Conference on Machine Learning, 2018


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