5 citations · 5 across the 2 of their papers we have counts for
3 papers
Improving Multimodal Interactive Agents with Reinforcement Learning from Human Feedback
Josh Abramson, Arun Ahuja, Federico Carnevale +16
An important goal in artificial intelligence is to create agents that can both interact naturally with humans and learn from their feedback. Here we demonstrate how to use reinforc…
Formalising Concepts as Grounded Abstractions
Stephen Clark, Alexander Lerchner, Tamara von Glehn +4
The notion of concept has been studied for centuries, by philosophers, linguists, cognitive scientists, and researchers in artificial intelligence (Margolis & Laurence, 1999). Ther…
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…