The BabyVLM Workshop: Toward Developmentally Plausible Multimodal Systems
Abstract
The BabyVLM Workshop at NeurIPS 2026 establishes a multidisciplinary forum to address the sample-efficiency gap between multimodal language models and human infants in their ability to learn language. Bringing together researchers from multimodal machine learning, cognitive science, and developmental psychology, the workshop explores how grounding language in other modalities can unlock data-efficient learning. It features keynotes and panels from senior scholars to foster a community centered on learnability, human-inspired AI evaluation, and longitudinal, egocentric learning. The event will also mark the official kickoff and tutorial for the BabyVLM Challenge, a competition explicitly designed to catalyze the development and fine-grained evaluation of small, sample-efficient vision-language models.