Search Results for author: Nathaniel Wong

Found 7 papers, 1 papers with code

Grounded Language Learning Fast and Slow

1 code implementation ICLR 2021 Felix Hill, Olivier Tieleman, Tamara von Glehn, Nathaniel Wong, Hamza Merzic, Stephen Clark

Recent work has shown that large text-based neural language models, trained with conventional supervised learning objectives, acquire a surprising propensity for few- and one-shot learning.

Grounded language learning Meta-Learning +1

Human Instruction-Following with Deep Reinforcement Learning via Transfer-Learning from Text

no code implementations19 May 2020 Felix Hill, Sona Mokra, Nathaniel Wong, Tim Harley

Here, we propose a conceptually simple method for training instruction-following agents with deep RL that are robust to natural human instructions.

Language Modelling reinforcement-learning +2

Robust Instruction-Following in a Situated Agent via Transfer-Learning from Text

no code implementations25 Sep 2019 Felix Hill, Sona Mokra, Nathaniel Wong, Tim Harley

We address this issue by integrating language encoders that are pretrained on large text corpora into a situated, instruction-following agent.

Representation Learning Transfer Learning

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