Modeling Others using Oneself in Multi-Agent Reinforcement Learning. - Roberta Raileanu; Emily Denton; Arthur Szlam; Rob Fergus (ICML, 2018)

Backplay: "Man muss immer umkehren". - Cinjon Resnick; Roberta Raileanu; Sanyam Kapoor; Alex Peysakhovich; Kyunghyun Cho; Joan Bruna (CoRR, 2018)

RIDE: Rewarding Impact-Driven Exploration for Procedurally-Generated Environments. - Roberta Raileanu; Tim Rocktäschel (ICLR, 2020)

Fast Adaptation to New Environments via Policy-Dynamics Value Functions. - Roberta Raileanu; Maxwell Goldstein; Arthur Szlam; Rob Fergus (ICML, 2020)

The NetHack Learning Environment. - Heinrich Küttler; Nantas Nardelli; Alexander H. Miller; Roberta Raileanu; Marco Selvatici; Edward Grefenstette; Tim Rocktäschel (NeurIPS, 2020)

Automatic Data Augmentation for Generalization in Deep Reinforcement Learning. - Roberta Raileanu; Maxwell Goldstein; Denis Yarats; Ilya Kostrikov; Rob Fergus (CoRR, 2020)

Fast Adaptation via Policy-Dynamics Value Functions. - Roberta Raileanu; Maxwell Goldstein; Arthur Szlam; Rob Fergus (CoRR, 2020)

Learning with AMIGo: Adversarially Motivated Intrinsic Goals. - Andres Campero; Roberta Raileanu; Heinrich Küttler; Joshua B. Tenenbaum; Tim Rocktäschel; Edward Grefenstette (ICLR, 2021)

Decoupling Value and Policy for Generalization in Reinforcement Learning. - Roberta Raileanu; Rob Fergus (ICML, 2021)

Insights From the NeurIPS 2021 NetHack Challenge. - Eric Hambro; Sharada P. Mohanty; Dmitrii Babaev; Minwoo Byeon; Dipam Chakraborty; Edward Grefenstette; Minqi Jiang; DaeJin Jo; Anssi Kanervisto; Jongmin Kim 006; Sungwoong Kim; Robert Kirk; et al. (NeurIPS (Competition and Demos), 2021)

Automatic Data Augmentation for Generalization in Reinforcement Learning. - Roberta Raileanu; Maxwell Goldstein; Denis Yarats; Ilya Kostrikov; Rob Fergus (NeurIPS, 2021)

Open-Ended Learning Leads to Generally Capable Agents. - Open Ended Learning Team; Adam Stooke; Anuj Mahajan; Catarina Barros; Charlie Deck; Jakob Bauer; Jakub Sygnowski; Maja Trebacz; Max Jaderberg; Michaël Mathieu; Nat McAleese; Nathalie Bradley-Schmieg; et al. (CoRR, 2021)

Towards More General and Adaptive Deep Reinforcement Learning Agents. - Roberta Raileanu (2021)

Dungeons and Data: A Large-Scale NetHack Dataset. - Eric Hambro; Roberta Raileanu; Danielle Rothermel; Vegard Mella; Tim Rocktäschel; Heinrich Küttler; Naila Murray (NeurIPS, 2022)

Exploration via Elliptical Episodic Bonuses. - Mikael Henaff; Roberta Raileanu; Minqi Jiang; Tim Rocktäschel (NeurIPS, 2022)

Improving Intrinsic Exploration with Language Abstractions. - Jesse Mu; Victor Zhong; Roberta Raileanu; Minqi Jiang; Noah D. Goodman; Tim Rocktäschel; Edward Grefenstette (NeurIPS, 2022)

Building a Subspace of Policies for Scalable Continual Learning. - Jean-Baptiste Gaya; Thang Doan; Lucas Caccia; Laure Soulier; Ludovic Denoyer; Roberta Raileanu (ICLR, 2023)

MAESTRO: Open-Ended Environment Design for Multi-Agent Reinforcement Learning. - Mikayel Samvelyan; Akbir Khan; Michael Dennis 001; Minqi Jiang; Jack Parker-Holder; Jakob Nicolaus Foerster; Roberta Raileanu; Tim Rocktäschel (ICLR, 2023)

Hyperparameters in Reinforcement Learning and How To Tune Them. - Theresa Eimer; Marius Lindauer; Roberta Raileanu (ICML, 2023)

A Study of Global and Episodic Bonuses for Exploration in Contextual MDPs. - Mikael Henaff; Minqi Jiang; Roberta Raileanu (ICML, 2023)

Improving Language Plasticity via Pretraining with Active Forgetting. - Yihong Chen; Kelly Marchisio; Roberta Raileanu; David Ifeoluwa Adelani; Pontus Lars Erik Saito Stenetorp; Sebastian Riedel 001; Mikel Artetxe (NeurIPS, 2023)

On the Importance of Exploration for Generalization in Reinforcement Learning. - Yiding Jiang; J. Zico Kolter; Roberta Raileanu (NeurIPS, 2023)

Toolformer: Language Models Can Teach Themselves to Use Tools. - Timo Schick; Jane Dwivedi-Yu; Roberto Dessì; Roberta Raileanu; Maria Lomeli; Eric Hambro; Luke Zettlemoyer; Nicola Cancedda; Thomas Scialom (NeurIPS, 2023)

Toolformer: Language Models Can Teach Themselves to Use Tools. - Timo Schick; Jane Dwivedi-Yu; Roberto Dessì; Roberta Raileanu; Maria Lomeli; Luke Zettlemoyer; Nicola Cancedda; Thomas Scialom (CoRR, 2023)

Challenges and Applications of Large Language Models. - Jean Kaddour; Joshua Harris; Maximilian Mozes; Herbie Bradley; Roberta Raileanu; Robert McHardy (CoRR, 2023)

Augmented Language Models: a Survey. - Grégoire Mialon; Roberto Dessì; Maria Lomeli; Christoforos Nalmpantis; Ramakanth Pasunuru; Roberta Raileanu; Baptiste Rozière; Timo Schick; Jane Dwivedi-Yu; Asli Celikyilmaz; Edouard Grave; Yann LeCun; et al. (Trans. Mach. Learn. Res., 2023)

Chain-of-Verification Reduces Hallucination in Large Language Models. - Shehzaad Dhuliawala; Mojtaba Komeili; Jing Xu; Roberta Raileanu; Xian Li 003; Asli Celikyilmaz; Jason Weston (ACL (Findings), 2024)

TOOLVERIFIER: Generalization to New Tools via Self-Verification. - Dheeraj Mekala; Jason Weston; Jack Lanchantin; Roberta Raileanu; Maria Lomeli; Jingbo Shang; Jane Dwivedi-Yu (EMNLP (Findings), 2024)

DreamCraft: Text-Guided Generation of Functional 3D Environments in Minecraft. - Sam Earle; Filippos Kokkinos; Yuhe Nie; Julian Togelius; Roberta Raileanu (FDG, 2024)

Understanding the Effects of RLHF on LLM Generalisation and Diversity. - Robert Kirk; Ishita Mediratta; Christoforos Nalmpantis; Jelena Luketina; Eric Hambro; Edward Grefenstette; Roberta Raileanu (ICLR, 2024)

Motif: Intrinsic Motivation from Artificial Intelligence Feedback. - Martin Klissarov; Pierluca D'Oro; Shagun Sodhani; Roberta Raileanu; Pierre-Luc Bacon; Pascal Vincent; Amy Zhang 001; Mikael Henaff (ICLR, 2024)

The Generalization Gap in Offline Reinforcement Learning. - Ishita Mediratta; Qingfei You; Minqi Jiang; Roberta Raileanu (ICLR, 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 (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)

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)

Are Large Language Models Strategic Decision Makers? A Study of Performance and Bias in Two-Player Non-Zero-Sum Games. - Nathan Herr; Fernando Acero; Roberta Raileanu; María Pérez-Ortiz 001; Zhibin Li 001 (CoRR, 2024)

Source2Synth: Synthetic Data Generation and Curation Grounded in Real Data Sources. - Alisia Maria Lupidi; Carlos Gemmell; Nicola Cancedda; Jane Dwivedi-Yu; Jason Weston; Jakob N. Foerster; Roberta Raileanu; Maria Lomeli (CoRR, 2024)

MaestroMotif: Skill Design from Artificial Intelligence Feedback. - Martin Klissarov; Mikael Henaff; Roberta Raileanu; Shagun Sodhani; Pascal Vincent; Amy Zhang 001; Pierre-Luc Bacon; Doina Precup; Marlos C. Machado; Pierluca D'Oro (ICLR, 2025)

MLGym: A New Framework and Benchmark for Advancing AI Research Agents. - Deepak Nathani; Lovish Madaan; Nicholas Roberts; Nikolay Bashlykov; Ajay Menon; Vincent Moens; Amar Budhiraja; Despoina Magka; Vladislav Vorotilov; Gaurav Chaurasia; Dieuwke Hupkes; Ricardo Silveira Cabral; et al. (CoRR, 2025)

Sparks of Science: Hypothesis Generation Using Structured Paper Data. - Charles O'Neill; Tirthankar Ghosal; Roberta Raileanu; Mike Walmsley; Thang D. Bui; Kevin Schawinski; Ioana Ciuca (CoRR, 2025)

LLM-First Search: Self-Guided Exploration of the Solution Space. - Nathan Herr; Tim Rocktäschel; Roberta Raileanu (CoRR, 2025)

The Automated LLM Speedrunning Benchmark: Reproducing NanoGPT Improvements. - Bingchen Zhao; Despoina Magka; Minqi Jiang; Xian Li; Roberta Raileanu; Tatiana Shavrina; Jean-Christophe Gagnon-Audet; Kelvin Niu; Shagun Sodhani; Michael Shvartsman; Andrei Lupu; Alisia Maria Lupidi; et al. (CoRR, 2025)

AI Research Agents for Machine Learning: Search, Exploration, and Generalization in MLE-bench. - Edan Toledo; Karen Hambardzumyan; Martin Josifoski; Rishi Hazra; Nicolas Mario Baldwin; Alexis Audran-Reiss; Michael Kuchnik; Despoina Magka; Minqi Jiang; Alisia Maria Lupidi; Andrei Lupu; Roberta Raileanu; et al. (CoRR, 2025)