Grefenstette, Edward

54 publications

ICLR 2025 Procedural Knowledge in Pretraining Drives Reasoning in Large Language Models Laura Ruis, Maximilian Mozes, Juhan Bae, Siddhartha Rao Kamalakara, Dwaraknath Gnaneshwar, Acyr Locatelli, Robert Kirk, Tim Rocktäschel, Edward Grefenstette, Max Bartolo

ICMLW 2024 Assessing the Zero-Shot Capabilities of LLMs for Action Evaluation in RL Eduardo Pignatelli, Johan Ferret, Davide Paglieri, Samuel Coward, Tim Rocktäschel, Edward Grefenstette, Laura Toni

ICML 2024 Debating with More Persuasive LLMs Leads to More Truthful Answers Akbir Khan, John Hughes, Dan Valentine, Laura Ruis, Kshitij Sachan, Ansh Radhakrishnan, Edward Grefenstette, Samuel R. Bowman, Tim Rocktäschel, Ethan Perez

ICLR 2024 H-GAP: Humanoid Control with a Generalist Planner Zhengyao Jiang, Yingchen Xu, Nolan Wagener, Yicheng Luo, Michael Janner, Edward Grefenstette, Tim Rocktäschel, Yuandong Tian

ICLR 2024 Mechanistically Analyzing the Effects of Fine-Tuning on Procedurally Defined Tasks Samyak Jain, Robert Kirk, Ekdeep Singh Lubana, Robert P. Dick, Hidenori Tanaka, Tim Rocktäschel, Edward Grefenstette, David Krueger

ICLRW 2024 Mechanistically Analyzing the Effects of Fine-Tuning on Procedurally Defined Tasks Samyak Jain, Robert Kirk, Ekdeep Singh Lubana, Robert P. Dick, Hidenori Tanaka, Tim Rocktäschel, Edward Grefenstette, David Krueger

ICLR 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

JAIR 2023 A Survey of Zero-Shot Generalisation in Deep Reinforcement Learning Robert Kirk, Amy Zhang, Edward Grefenstette, Tim Rocktäschel

ICMLW 2023 Do LLMs Selectively Encode the Goal of an Agent's Reach? Laura Ruis, Arduin Findeis, Herbie Bradley, Hossein A. Rahmani, Kyoung Whan Choe, Edward Grefenstette, Tim Rocktäschel

ICLR 2023 Efficient Planning in a Compact Latent Action Space Zhengyao Jiang, Tianjun Zhang, Michael Janner, Yueying Li, Tim Rocktäschel, Edward Grefenstette, Yuandong Tian

NeurIPSW 2023 H-GAP: Humanoid Control with a Generalist Planner Zhengyao Jiang, Yingchen Xu, Nolan Wagener, Yicheng Luo, Michael Janner, Edward Grefenstette, Tim Rocktäschel, Yuandong Tian

NeurIPSW 2023 How Does Fine-Tuning Affect Your Model? Mechanistic Analysis on Procedural Tasks Samyak Jain, Robert Kirk, Ekdeep Singh Lubana, Robert P. Dick, Hidenori Tanaka, Tim Rocktäschel, Edward Grefenstette, David Krueger

NeurIPSW 2023 How Does Fine-Tuning Affect Your Model? Mechanistic Analysis on Procedural Tasks Samyak Jain, Robert Kirk, Ekdeep Singh Lubana, Robert P. Dick, Hidenori Tanaka, Tim Rocktäschel, Edward Grefenstette, David Krueger

NeurIPSW 2023 Leading the Pack: N-Player Opponent Shaping Alexandra Souly, Timon Willi, Akbir Khan, Robert Kirk, Chris Lu, Edward Grefenstette, Tim Rocktäschel

NeurIPSW 2023 Minimax: Efficient Baselines for Autocurricula in JAX Minqi Jiang, Michael D Dennis, Edward Grefenstette, Tim Rocktäschel

ICLR 2023 Optimal Transport for Offline Imitation Learning Yicheng Luo, Zhengyao Jiang, Samuel Cohen, Edward Grefenstette, Marc Peter Deisenroth

NeurIPS 2023 The Goldilocks of Pragmatic Understanding: Fine-Tuning Strategy Matters for Implicature Resolution by LLMs Laura Ruis, Akbir Khan, Stella Biderman, Sara Hooker, Tim Rocktäschel, Edward Grefenstette

NeurIPSW 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

ICLRW 2022 A Study of Off-Policy Learning in Environments with Procedural Content Generation Andy Ehrenberg, Robert Kirk, Minqi Jiang, Edward Grefenstette, Tim Rocktäschel

NeurIPSW 2022 Efficient Planning in a Compact Latent Action Space Zhengyao Jiang, Tianjun Zhang, Michael Janner, Yueying Li, Tim Rocktäschel, Edward Grefenstette, Yuandong Tian

ICML 2022 Evolving Curricula with Regret-Based Environment Design Jack Parker-Holder, Minqi Jiang, Michael Dennis, Mikayel Samvelyan, Jakob Foerster, Edward Grefenstette, Tim Rocktäschel

NeurIPS 2022 Grounding Aleatoric Uncertainty for Unsupervised Environment Design Minqi Jiang, Michael Dennis, Jack Parker-Holder, Andrei Lupu, Heinrich Küttler, Edward Grefenstette, Tim Rocktäschel, Jakob Foerster

CoLLAs 2022 Hierarchical Kickstarting for Skill Transfer in Reinforcement Learning Michael Matthews, Mikayel Samvelyan, Jack Parker-holder, Edward Grefenstette, Tim Rocktäschel

NeurIPS 2022 Improving Intrinsic Exploration with Language Abstractions Jesse Mu, Victor Zhong, Roberta Raileanu, Minqi Jiang, Noah Goodman, Tim Rocktäschel, Edward Grefenstette

NeurIPS 2022 Improving Policy Learning via Language Dynamics Distillation Victor Zhong, Jesse Mu, Luke Zettlemoyer, Edward Grefenstette, Tim Rocktäschel

NeurIPS 2022 Learning General World Models in a Handful of Reward-Free Deployments Yingchen Xu, Jack Parker-Holder, Aldo Pacchiano, Philip Ball, Oleh Rybkin, S Roberts, Tim Rocktäschel, Edward Grefenstette

NeurIPSW 2022 Optimal Transport for Offline Imitation Learning Yicheng Luo, Zhengyao Jiang, Samuel Cohen, Edward Grefenstette, Marc Peter Deisenroth

ICLRW 2022 SkillHack: A Benchmark for Skill Transfer in Open-Ended Reinforcement Learning Michael Matthews, Mikayel Samvelyan, Jack Parker-Holder, Edward Grefenstette, Tim Rocktäschel

NeurIPSW 2021 Graph Backup: Data Efficient Backup Exploiting Markovian Data Zhengyao Jiang, Tianjun Zhang, Robert Kirk, Tim Rocktäschel, Edward Grefenstette

NeurIPSW 2021 Grounding Aleatoric Uncertainty in Unsupervised Environment Design Minqi Jiang, Michael D Dennis, Jack Parker-Holder, Andrei Lupu, Heinrich Kuttler, Edward Grefenstette, Tim Rocktäschel, Jakob Nicolaus Foerster

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

ICML 2021 Prioritized Level Replay Minqi Jiang, Edward Grefenstette, Tim Rocktäschel

NeurIPS 2021 Replay-Guided Adversarial Environment Design Minqi Jiang, Michael Dennis, Jack Parker-Holder, Jakob Foerster, Edward Grefenstette, Tim Rocktäschel

NeurIPSW 2021 Return Dispersion as an Estimator of Learning Potential for Prioritized Level Replay Iryna Korshunova, Minqi Jiang, Jack Parker-Holder, Tim Rocktäschel, Edward Grefenstette

NeurIPSW 2021 Return Dispersion as an Estimator of Learning Potential for Prioritized Level Replay Iryna Korshunova, Minqi Jiang, Jack Parker-Holder, Tim Rocktäschel, Edward Grefenstette

NeurIPSW 2021 That Escalated Quickly: Compounding Complexity by Editing Levels at the Frontier of Agent Capabilities Jack Parker-Holder, Minqi Jiang, Michael D Dennis, Mikayel Samvelyan, Jakob Nicolaus Foerster, Edward Grefenstette, Tim Rocktäschel

AAAI 2020 Differentiable Reasoning on Large Knowledge Bases and Natural Language Pasquale Minervini, Matko Bosnjak, Tim Rocktäschel, Sebastian Riedel, Edward Grefenstette

ICML 2020 Learning Reasoning Strategies in End-to-End Differentiable Proving Pasquale Minervini, Sebastian Riedel, Pontus Stenetorp, Edward Grefenstette, Tim Rocktäschel

ICLR 2020 RTFM: Generalising to New Environment Dynamics via Reading Victor Zhong, Tim Rocktäschel, Edward Grefenstette

NeurIPS 2020 The NetHack Learning Environment Heinrich Küttler, Nantas Nardelli, Alexander Miller, Roberta Raileanu, Marco Selvatici, Edward Grefenstette, Tim Rocktäschel

IJCAI 2019 A Survey of Reinforcement Learning Informed by Natural Language Jelena Luketina, Nantas Nardelli, Gregory Farquhar, Jakob N. Foerster, Jacob Andreas, Edward Grefenstette, Shimon Whiteson, Tim Rocktäschel

ICLR 2019 Analysing Mathematical Reasoning Abilities of Neural Models David Saxton, Edward Grefenstette, Felix Hill, Pushmeet Kohli

ICML 2019 CompILE: Compositional Imitation Learning and Execution Thomas Kipf, Yujia Li, Hanjun Dai, Vinicius Zambaldi, Alvaro Sanchez-Gonzalez, Edward Grefenstette, Pushmeet Kohli, Peter Battaglia

CVPR 2019 Knowing When to Stop: Evaluation and Verification of Conformity to Output-Size Specifications Chenglong Wang, Rudy Bunel, Krishnamurthy Dvijotham, Po-Sen Huang, Edward Grefenstette, Pushmeet Kohli

ICLR 2019 Learning to Understand Goal Specifications by Modelling Reward Dzmitry Bahdanau, Felix Hill, Jan Leike, Edward Hughes, Arian Hosseini, Pushmeet Kohli, Edward Grefenstette

ICLR 2018 Can Neural Networks Understand Logical Entailment? Richard Evans, David Saxton, David Amos, Pushmeet Kohli, Edward Grefenstette

JAIR 2018 Learning Explanatory Rules from Noisy Data Richard Evans, Edward Grefenstette

IJCAI 2018 Learning Explanatory Rules from Noisy Data (Extended Abstract) Richard Evans, Edward Grefenstette

ICML 2017 Discovering Discrete Latent Topics with Neural Variational Inference Yishu Miao, Edward Grefenstette, Phil Blunsom

ICLR 2017 Learning to Compose Words into Sentences with Reinforcement Learning Dani Yogatama, Phil Blunsom, Chris Dyer, Edward Grefenstette, Wang Ling

ICLR 2017 The Neural Noisy Channel Lei Yu, Phil Blunsom, Chris Dyer, Edward Grefenstette, Tomás Kociský

ICLR 2016 Reasoning About Entailment with Neural Attention Tim Rocktäschel, Edward Grefenstette, Karl Moritz Hermann, Tomás Kociský, Phil Blunsom

NeurIPS 2015 Learning to Transduce with Unbounded Memory Edward Grefenstette, Karl Moritz Hermann, Mustafa Suleyman, Phil Blunsom

NeurIPS 2015 Teaching Machines to Read and Comprehend Karl Moritz Hermann, Tomas Kocisky, Edward Grefenstette, Lasse Espeholt, Will Kay, Mustafa Suleyman, Phil Blunsom