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08/21/2023
Stabilizing Unsupervised Environment Design with a Learned Adversary
A key challenge in training generally-capable agents is the design of tr...
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03/06/2023
MAESTRO: Open-Ended Environment Design for Multi-Agent Reinforcement Learning
Open-ended learning methods that automatically generate a curriculum of ...
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01/18/2023
Human-Timescale Adaptation in an Open-Ended Task Space
Foundation models have shown impressive adaptation and scalability in su...
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11/15/2022
General Intelligence Requires Rethinking Exploration
We are at the cusp of a transition from "learning from data" to "learnin...
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11/01/2022
Dungeons and Data: A Large-Scale NetHack Dataset
Recent breakthroughs in the development of agents to solve challenging s...
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10/26/2022
Large language models are not zero-shot communicators
Despite widespread use of LLMs as conversational agents, evaluations of ...
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10/23/2022
Learning General World Models in a Handful of Reward-Free Deployments
Building generally capable agents is a grand challenge for deep reinforc...
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10/11/2022
Exploration via Elliptical Episodic Bonuses
In recent years, a number of reinforcement learning (RL) methods have be...
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09/30/2022
Improving Policy Learning via Language Dynamics Distillation
Recent work has shown that augmenting environments with language descrip...
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08/22/2022
Efficient Planning in a Compact Latent Action Space
While planning-based sequence modelling methods have shown great potenti...
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07/23/2022
Hierarchical Kickstarting for Skill Transfer in Reinforcement Learning
Practising and honing skills forms a fundamental component of how humans...
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07/13/2022
GriddlyJS: A Web IDE for Reinforcement Learning
Progress in reinforcement learning (RL) research is often driven by the ...
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07/11/2022
Grounding Aleatoric Uncertainty in Unsupervised Environment Design
Adaptive curricula in reinforcement learning (RL) have proven effective ...
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05/31/2022
Graph Backup: Data Efficient Backup Exploiting Markovian Transitions
The successes of deep Reinforcement Learning (RL) are limited to setting...
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03/22/2022
Insights From the NeurIPS 2021 NetHack Challenge
In this report, we summarize the takeaways from the first NeurIPS 2021 N...
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03/02/2022
Evolving Curricula with Regret-Based Environment Design
It remains a significant challenge to train generally capable agents wit...
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02/17/2022
Improving Intrinsic Exploration with Language Abstractions
Reinforcement learning (RL) agents are particularly hard to train when r...
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11/18/2021
A Survey of Generalisation in Deep Reinforcement Learning
The study of generalisation in deep Reinforcement Learning (RL) aims to ...
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10/06/2021
Replay-Guided Adversarial Environment Design
Deep reinforcement learning (RL) agents may successfully generalize to n...
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09/27/2021
MiniHack the Planet: A Sandbox for Open-Ended Reinforcement Learning Research
The progress in deep reinforcement learning (RL) is heavily driven by th...
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07/26/2021
Don't Sweep your Learning Rate under the Rug: A Closer Look at Cross-modal Transfer of Pretrained Transformers
Self-supervised pre-training of large-scale transformer models on text c...
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02/08/2021
Grid-to-Graph: Flexible Spatial Relational Inductive Biases for Reinforcement Learning
Although reinforcement learning has been successfully applied in many do...
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10/08/2020
Prioritized Level Replay
Simulated environments with procedurally generated content have become p...
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10/05/2020
My Body is a Cage: the Role of Morphology in Graph-Based Incompatible Control
Multitask Reinforcement Learning is a promising way to obtain models wit...
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10/01/2020
How to Motivate Your Dragon: Teaching Goal-Driven Agents to Speak and Act in Fantasy Worlds
We seek to create agents that both act and communicate with other agents...
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09/04/2020
KILT: a Benchmark for Knowledge Intensive Language Tasks
Challenging problems such as open-domain question answering, fact checki...
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07/17/2020
WordCraft: An Environment for Benchmarking Commonsense Agents
The ability to quickly solve a wide range of real-world tasks requires a...
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07/13/2020
Learning Reasoning Strategies in End-to-End Differentiable Proving
Attempts to render deep learning models interpretable, data-efficient, a...
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06/24/2020
The NetHack Learning Environment
Progress in Reinforcement Learning (RL) algorithms goes hand-in-hand wit...
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06/22/2020
Learning with AMIGo: Adversarially Motivated Intrinsic Goals
A key challenge for reinforcement learning (RL) consists of learning in ...
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05/22/2020
Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks
Large pre-trained language models have been shown to store factual knowl...
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05/10/2020
How Context Affects Language Models' Factual Predictions
When pre-trained on large unsupervised textual corpora, language models ...
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04/16/2020
There is Strength in Numbers: Avoiding the Hypothesis-Only Bias in Natural Language Inference via Ensemble Adversarial Training
Natural Language Inference (NLI) datasets contain annotation artefacts r...
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02/27/2020
RIDE: Rewarding Impact-Driven Exploration for Procedurally-Generated Environments
Exploration in sparse reward environments remains one of the key challen...
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12/17/2019
Differentiable Reasoning on Large Knowledge Bases and Natural Language
Reasoning with knowledge expressed in natural language and Knowledge Bas...
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11/20/2019
Generating Interactive Worlds with Text
Procedurally generating cohesive and interesting game environments is ch...
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11/09/2019
How Decoding Strategies Affect the Verifiability of Generated Text
Language models are of considerable importance. They are used for pretra...
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10/18/2019
RTFM: Generalising to Novel Environment Dynamics via Reading
Obtaining policies that can generalise to new environments in reinforcem...
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10/09/2019
MVFST-RL: An Asynchronous RL Framework for Congestion Control with Delayed Actions
Effective network congestion control strategies are key to keeping the I...
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10/08/2019
TorchBeast: A PyTorch Platform for Distributed RL
TorchBeast is a platform for reinforcement learning (RL) research in PyT...
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09/03/2019
Language Models as Knowledge Bases?
Recent progress in pretraining language models on large textual corpora ...
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06/14/2019
NLProlog: Reasoning with Weak Unification for Question Answering in Natural Language
Rule-based models are attractive for various tasks because they inherent...
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06/12/2019
Neural Variational Inference For Estimating Uncertainty in Knowledge Graph Embeddings
Recent advances in Neural Variational Inference allowed for a renaissanc...
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06/10/2019
A Survey of Reinforcement Learning Informed by Natural Language
To be successful in real-world tasks, Reinforcement Learning (RL) needs ...
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03/07/2019
Learning to Speak and Act in a Fantasy Text Adventure Game
We introduce a large scale crowdsourced text adventure game as a researc...
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12/04/2018
e-SNLI: Natural Language Inference with Natural Language Explanations
In order for machine learning to garner widespread public adoption, mode...
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12/04/2018
e-SNLI: Natural Language Inference withNatural Language Explanations
In order for machine learning to garner widespread public adoption, mode...
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11/20/2018
Stable Opponent Shaping in Differentiable Games
A growing number of learning methods are actually games which optimise m...
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08/28/2018
Interpretation of Natural Language Rules in Conversational Machine Reading
Most work in machine reading focuses on question answering problems wher...
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07/21/2018