Bridging the data gap between children and large language models

Abstract

Large language models show intriguing emergent behaviors, yet they receive around 4-5 orders of magnitude more language data than human children. What accounts for this vast difference in sample efficiency? Candidate explanations include children’s pre-existing conceptual structures, their use of multimodal grounding, and the interactive, social nature of their input.

Topics & Concepts