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)

MiniHack the Planet: A Sandbox for Open-Ended Reinforcement Learning Research. - Mikayel Samvelyan; Robert Kirk; Vitaly Kurin; Jack Parker-Holder; Minqi Jiang; Eric Hambro; Fabio Petroni; Heinrich Küttler; Edward Grefenstette; Tim Rocktäschel (NeurIPS Datasets and Benchmarks, 2021)

GPflux: A Library for Deep Gaussian Processes. - Vincent Dutordoir; Hugh Salimbeni; Eric Hambro; John McLeod; Felix Leibfried; Artem Artemev; Mark van der Wilk; James Hensman; Marc Peter Deisenroth; S. T. John (CoRR, 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)

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)

LLaMA: Open and Efficient Foundation Language Models. - Hugo Touvron; Thibaut Lavril; Gautier Izacard; Xavier Martinet; Marie-Anne Lachaux; Timothée Lacroix; Baptiste Rozière; Naman Goyal 001; Eric Hambro; Faisal Azhar; Aurélien Rodriguez; Armand Joulin; et al. (CoRR, 2023)

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)

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)

Know When To Stop: A Study of Semantic Drift in Text Generation. - Ava Spataru; Eric Hambro; Elena Voita; Nicola Cancedda (NAACL-HLT, 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)