3.1k citations · 5.1k across the 43 of their papers we have counts for
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Differentiable Reasoning on Large Knowledge Bases and Natural Language
Pasquale Minervini, Matko Bošnjak, Tim Rocktäschel +2
Reasoning with knowledge expressed in natural language and Knowledge Bases (KBs) is a major challenge for Artificial Intelligence, with applications in machine reading, dialogue, a…
Generating Interactive Worlds with Text
Angela Fan, Jack Urbanek, Pratik Ringshia +8
Procedurally generating cohesive and interesting game environments is challenging and time-consuming. In order for the relationships between the game elements to be natural, common…
How Decoding Strategies Affect the Verifiability of Generated Text
Luca Massarelli, Fabio Petroni, Aleksandra Piktus +5
Recent progress in pre-trained language models led to systems that are able to generate text of an increasingly high quality. While several works have investigated the fluency and…
TorchBeast: A PyTorch Platform for Distributed RL
Heinrich Küttler, Nantas Nardelli, Thibaut Lavril +4
TorchBeast is a platform for reinforcement learning (RL) research in PyTorch. It implements a version of the popular IMPALA algorithm for fast, asynchronous, parallel training of R…
RTFM: Generalising to Novel Environment Dynamics via Reading
Victor Zhong, Tim Rocktäschel, Edward Grefenstette
Obtaining policies that can generalise to new environments in reinforcement learning is challenging. In this work, we demonstrate that language understanding via a reading policy l…
Language Models as Knowledge Bases?
Fabio Petroni, Tim Rocktäschel, Patrick Lewis +4
Recent progress in pretraining language models on large textual corpora led to a surge of improvements for downstream NLP tasks. Whilst learning linguistic knowledge, these models…
NLProlog: Reasoning with Weak Unification for Question Answering in Natural Language
Leon Weber, Pasquale Minervini, Jannes Münchmeyer +2
Rule-based models are attractive for various tasks because they inherently lead to interpretable and explainable decisions and can easily incorporate prior knowledge. However, such…
A Survey of Reinforcement Learning Informed by Natural Language
Jelena Luketina, Nantas Nardelli, Gregory Farquhar +5
To be successful in real-world tasks, Reinforcement Learning (RL) needs to exploit the compositional, relational, and hierarchical structure of the world, and learn to transfer it…
Neural Variational Inference For Estimating Uncertainty in Knowledge Graph Embeddings
Alexander I. Cowen-Rivers, Pasquale Minervini, Tim Rocktaschel +3
Recent advances in Neural Variational Inference allowed for a renaissance in latent variable models in a variety of domains involving high-dimensional data. While traditional varia…
Learning to Speak and Act in a Fantasy Text Adventure Game
Jack Urbanek, Angela Fan, Siddharth Karamcheti +7
We introduce a large scale crowdsourced text adventure game as a research platform for studying grounded dialogue. In it, agents can perceive, emote, and act whilst conducting dial…