984 citations · 3.3k across the 41 of their papers we have counts for
4 papers · 1 filter
Attention over learned object embeddings enables complex visual reasoning
David Ding, Felix Hill, Adam Santoro +2
Neural networks have achieved success in a wide array of perceptual tasks but often fail at tasks involving both perception and higher-level reasoning. On these more challenging ta…
Grounded Language Learning Fast and Slow
Felix Hill, Olivier Tieleman, Tamara von Glehn +3
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…
Probing Emergent Semantics in Predictive Agents via Question Answering
Abhishek Das, Federico Carnevale, Hamza Merzic +8
Recent work has shown how predictive modeling can endow agents with rich knowledge of their surroundings, improving their ability to act in complex environments. We propose questio…
Human Instruction-Following with Deep Reinforcement Learning via Transfer-Learning from Text
Felix Hill, Sona Mokra, Nathaniel Wong +1
Recent work has described neural-network-based agents that are trained with reinforcement learning (RL) to execute language-like commands in simulated worlds, as a step towards an…