Edward Grefenstette

发表

A Convolutional Neural Network for Modelling Sentences

Phil Blunsom, Edward Grefenstette, Nal Kalchbrenner, 2014, ACL.

Hybrid computing using a neural network with dynamic external memory

Sergio Gomez Colmenarejo, Alex Graves, Demis Hassabis, 2016, Nature.

A Deep Architecture for Semantic Parsing pdf

Nando de Freitas, Phil Blunsom, Edward Grefenstette, 2014, ACL 2014.

Teaching Machines to Read and Comprehend

Phil Blunsom, Tomás Kociský, Edward Grefenstette, 2015, NIPS.

Learning to Transduce with Unbounded Memory

Phil Blunsom, Edward Grefenstette, Karl Moritz Hermann, 2015, NIPS.

Analysing Mathematical Reasoning Abilities of Neural Models pdf

Pushmeet Kohli, Felix Hill, Edward Grefenstette, 2019, ICLR.

Experimental Support for a Categorical Compositional Distributional Model of Meaning pdf

Mehrnoosh Sadrzadeh, Edward Grefenstette, Edward Grefenstette, 2011, EMNLP.

Proceedings of the 3rd Workshop on Continuous Vector Space Models and their Compositionality

Hugo Larochelle, Alexandre Allauzen, Edward Grefenstette, 2015, CVSC.

Multi-Step Regression Learning for Compositional Distributional Semantics pdf

Mehrnoosh Sadrzadeh, Georgiana Dinu, Edward Grefenstette, 2013, IWCS.

Latent Predictor Networks for Code Generation pdf

Wang Ling, Phil Blunsom, Tomás Kociský, 2016, ACL.

Concrete Sentence Spaces for Compositional Distributional Models of Meaning pdf

Stephen Clark, Mehrnoosh Sadrzadeh, Stephen G. Pulman, 2010, IWCS.

Learning to Compute Word Embeddings On the Fly pdf

Pascal Vincent, Yoshua Bengio, Edward Grefenstette, 2017, ArXiv.

Towards a Formal Distributional Semantics: Simulating Logical Calculi with Tensors pdf

Edward Grefenstette, Edward Grefenstette, 2013, *SEMEVAL.

CompILE: Compositional Imitation Learning and Execution

Pushmeet Kohli, Edward Grefenstette, Hanjun Dai, 2018, ICML.

EACL 2014 14th Conference of the European Chapter of the Association for Computational Linguistics Proceedings of the 2nd Workshop on Continuous Vector Space Models and their Compositionality (CVSC)

Hugo Larochelle, Alexandre Allauzen, Raffaella Bernardi, 2014 .

TITLE : Producing Figurative Language PAPER TITLE : An Emergent Model of Metaphors as Transformations of Vector Spaces

Edward Grefenstette, 2014 .

Table of Contents Distributional Semantics from Text and Images Reranking Bilingually Extracted Paraphrases Using Monolingual Distributional Similarity Encoding Syntactic Dependencies by Vector Permutation Workshop Program Attribute-related Meaning Representations for Adjective- Noun Phrases in a Si

Benjamin Van Durme, Mirella Lapata, Chris Callison-Burch, 2022 .

Learning to Follow Language Instructions with Adversarial Reward Induction pdf

Pushmeet Kohli, Felix Hill, Edward Grefenstette, 2018, ArXiv.

A Survey of Reinforcement Learning Informed by Natural Language

Shimon Whiteson, Jacob Andreas, Edward Grefenstette, 2019, IJCAI.

Jointly Learning "What" and "How" from Instructions and Goal-States

Pushmeet Kohli, Felix Hill, Edward Grefenstette, 2018, ICLR.

Semantic Parsing with Semi-Supervised Sequential Autoencoders

Chris Dyer, Edward Grefenstette, P. Blunsom, 2016, EMNLP.

Scalable Neural Theorem Proving on Knowledge Bases and Natural Language

Edward Grefenstette, Pasquale Minervini, Sebastian Riedel, 2018 .

S KILL H ACK : A B ENCHMARK FOR S KILL T RANSFER IN O PEN -E NDED R EINFORCEMENT L EARNING

Edward Grefenstette, Tim Rocktäschel, Jack Parker-Holder, 2022 .

Graph Backup: Data Efficient Backup Exploiting Markovian Transitions

Edward Grefenstette, Tim Rocktaschel, Tianjun Zhang, 2022, ArXiv.

Grounding Aleatoric Uncertainty in Unsupervised Environment Design

Jakob N. Foerster, Edward Grefenstette, Jack Parker-Holder, 2022, 2207.05219.

Hierarchical Kickstarting for Skill Transfer in Reinforcement Learning

Edward Grefenstette, Jack Parker-Holder, Tim Rocktaschel, 2022, 2207.11584.

Efficient Planning in a Compact Latent Action Space

Michael Janner, Edward Grefenstette, Tim Rocktaschel, 2022, International Conference on Learning Representations.

Hierarchical Kickstarting for Skill Transfer in Reinforcement Learning

Edward Grefenstette, Jack Parker-Holder, Tim Rocktaschel, 2022, CoLLAs.

Improving Policy Learning via Language Dynamics Distillation

Luke Zettlemoyer, Edward Grefenstette, Victor Zhong, 2022, NeurIPS.

Learning General World Models in a Handful of Reward-Free Deployments

Stephen J. Roberts, Philip J. Ball, Edward Grefenstette, 2022, NeurIPS.

Grounding Aleatoric Uncertainty in Unsupervised Environment Design

Edward Grefenstette, Jack Parker-Holder, A. Lupu, 2022, NeurIPS.

Large language models are not zero-shot communicators

Stella Rose Biderman, Edward Grefenstette, Sara Hooker, 2022, ArXiv.

General intelligence requires rethinking exploration

Edward Grefenstette, Tim Rocktaschel, Minqi Jiang, 2022, Royal Society Open Science.

Improving Intrinsic Exploration with Language Abstractions

Noah D. Goodman, Edward Grefenstette, Victor Zhong, 2022, NeurIPS.

The NarrativeQA Reading Comprehension Challenge

Chris Dyer, Phil Blunsom, Gábor Melis, 2017, TACL.

The Neural Noisy Channel pdf

Lei Yu, Chris Dyer, Phil Blunsom, 2016, ICLR.

Reasoning about Entailment with Neural Attention pdf

Phil Blunsom, Tomás Kociský, Edward Grefenstette, 2015, ICLR.

Discovering Discrete Latent Topics with Neural Variational Inference pdf

Phil Blunsom, Yishu Miao, Edward Grefenstette, 2017, ICML.

Generalized Inner Loop Meta-Learning pdf

Artem Molchanov, Kyunghyun Cho, Edward Grefenstette, 2019, ArXiv.

Learning Explanatory Rules from Noisy Data

Richard Evans, Edward Grefenstette, Edward Grefenstette, 2017, J. Artif. Intell. Res..

Learning Reasoning Strategies in End-to-End Differentiable Proving pdf

Edward Grefenstette, Pasquale Minervini, Sebastian Riedel, 2020, ICML.

A Survey of Generalisation in Deep Reinforcement Learning

Edward Grefenstette, Amy Zhang, Tim Rocktaschel, 2021, ArXiv.

Evolving Curricula with Regret-Based Environment Design

Edward Grefenstette, Jack Parker-Holder, Tim Rocktaschel, 2022, ICML.

Replay-Guided Adversarial Environment Design pdf

Edward Grefenstette, Tim Rocktaschel, Michael Dennis, 2021, NeurIPS.

MiniHack the Planet: A Sandbox for Open-Ended Reinforcement Learning Research pdf

Fabio Petroni, Edward Grefenstette, Tim Rocktäschel, 2021, NeurIPS Datasets and Benchmarks.

Prioritized Level Replay pdf

Edward Grefenstette, Tim Rocktäschel, Minqi Jiang, 2020, ICML.

The NetHack Learning Environment pdf

Edward Grefenstette, Tim Rocktaschel, Alexander H. Miller, 2020, NeurIPS.

RTFM: Generalising to Novel Environment Dynamics via Reading

Edward Grefenstette, Tim Rocktäschel, Victor Zhong, 2019, ArXiv.

Optimal Transport for Offline Imitation Learning

M. Deisenroth, Edward Grefenstette, Samuel Cohen, 2023, ICLR.

Learning to Understand Goal Specifications by Modelling Reward

Pushmeet Kohli, Felix Hill, Edward Grefenstette, 2018, ICLR.

A Survey of Zero-shot Generalisation in Deep Reinforcement Learning

Edward Grefenstette, Tim Rocktäschel, Amy Zhang, 2021, J. Artif. Intell. Res..

Category-theoretic quantitative compositional distributional models of natural language semantics pdf

Edward Grefenstette, Edward Grefenstette, 2013, ArXiv.

Efficient Planning in a Compact Latent Action Space

Michael Janner, Edward Grefenstette, Tim Rocktaschel, 2022, ICLR.

Differentiable Reasoning on Large Knowledge Bases and Natural Language

Edward Grefenstette, Pasquale Minervini, Sebastian Riedel, 2019, Knowledge Graphs for eXplainable Artificial Intelligence.

Learning with AMIGo: Adversarially Motivated Intrinsic Goals pdf

Joshua B. Tenenbaum, Edward Grefenstette, Tim Rocktäschel, 2020, ICLR.

Strength in Numbers: Trading-off Robustness and Computation via Adversarially-Trained Ensembles pdf

Pushmeet Kohli, Edward Grefenstette, Jonathan Uesato, 2018, ArXiv.

A quantum teleportation inspired algorithm produces sentence meaning from word meaning and grammatical structure pdf

Stephen Clark, Mehrnoosh Sadrzadeh, Stephen G. Pulman, 2013, ArXiv.

TorchBeast: A PyTorch Platform for Distributed RL pdf

Edward Grefenstette, Tim Rocktäschel, Heinrich Küttler, 2019, ArXiv.

Lambek vs. Lambek: Functorial vector space semantics and string diagrams for Lambek calculus

Mehrnoosh Sadrzadeh, Edward Grefenstette, Bob Coecke, 2013, Ann. Pure Appl. Log..

Concrete Models and Empirical Evaluations for the Categorical Compositional Distributional Model of Meaning

Mehrnoosh Sadrzadeh, Edward Grefenstette, Edward Grefenstette, 2015, CL.

A Type-Driven Tensor-Based Semantics for CCG

Stephen Clark, Edward Grefenstette, Jean Maillard, 2014, EACL 2014.

Experimenting with transitive verbs in a DisCoCat pdf

Mehrnoosh Sadrzadeh, Edward Grefenstette, Edward Grefenstette, 2011, GEMS.

A Compositional Distributional Semantics, Two Concrete Constructions, and Some Experimental Evaluations pdf

Mehrnoosh Sadrzadeh, Edward Grefenstette, Edward Grefenstette, 2011, QI.

Learning to Compose Words into Sentences with Reinforcement Learning pdf

Wang Ling, Chris Dyer, Phil Blunsom, 2016, ICLR.

Can Neural Networks Understand Logical Entailment? pdf

Richard Evans, Pushmeet Kohli, David Amos, 2018, ICLR.

Compositional Imitation Learning: Explaining and executing one task at a time pdf

Pushmeet Kohli, Edward Grefenstette, Hanjun Dai, 2018, ArXiv.

Insights From the NeurIPS 2021 NetHack Challenge

Edward Grefenstette, Nantas Nardelli, Jack Parker-Holder, 2022, NeurIPS.

“Not not bad” is not “bad”: A distributional account of negation pdf

Phil Blunsom, Edward Grefenstette, Karl Moritz Hermann, 2013, CVSM@ACL.

Deep Learning for Semantic Composition

Edward Grefenstette, Xiao-Dan Zhu, Edward Grefenstette, 2017, ACL.

Proceedings of the 1st Workshop on Representation Learning for NLP

Jason Weston, Shay B. Cohen, Kyunghyun Cho, 2016 .

higher: A Pytorch Meta-Learning Library

Kyunghyun Cho, Franziska Meier, Edward Grefenstette, 2020 .

Learning Explanatory Rules from Noisy Data (Extended Abstract)

Richard Evans, Edward Grefenstette, Edward Grefenstette, 2018, IJCAI.

The Goldilocks of Pragmatic Understanding: Fine-Tuning Strategy Matters for Implicature Resolution by LLMs

Edward Grefenstette, Sara Hooker, Tim Rocktaschel, 2022, 2210.14986.

Understanding the Effects of RLHF on LLM Generalisation and Diversity

Edward Grefenstette, Roberta Raileanu, Ishita Mediratta, 2023, ArXiv.

The NetHack Learning Environment pdf

Edward Grefenstette, Tim Rocktaschel, Alexander H. Miller, 2020, NeurIPS.

The 3rd Workshop on Continuous Vector Space Models and Their Compositionality (cvsc) Recursive Neural Networks Can Learn Logical Semantics Joint Semantic Relevance Learning with Text Data and Graph Knowledge Exploring the Effect of Semantic Similarity for Phrase-based Machine Translation Incremental

L. Bottou, Kristina Toutanova, Edward Grefenstette, 2022 .

RTFM: Generalising to New Environment Dynamics via Reading

Edward Grefenstette, Tim Rocktäschel, Victor Zhong, 2020, ICLR.

H-GAP: Humanoid Control with a Generalist Planner

Edward Grefenstette, Nolan Wagener, Tim Rocktaschel, 2023, ArXiv.

Assessing the Zero-Shot Capabilities of LLMs for Action Evaluation in RL

Edward Grefenstette, Johan Ferret, Eduardo Pignatelli, 2024, 2409.12798.