SocialGen: Modeling Multi-Human Social Interaction with Language Models
Journal:
arXiv
Published Date:
Mar 28, 2025
Abstract
Human interactions in everyday life are inherently social, involving
engagements with diverse individuals across various contexts. Modeling these
social interactions is fundamental to a wide range of real-world applications.
In this paper, we introduce SocialGen, the first unified motion-language model
capable of modeling interaction behaviors among varying numbers of individuals,
to address this crucial yet challenging problem. Unlike prior methods that are
limited to two-person interactions, we propose a novel social motion
representation that supports tokenizing the motions of an arbitrary number of
individuals and aligning them with the language space. This alignment enables
the model to leverage rich, pretrained linguistic knowledge to better
understand and reason about human social behaviors. To tackle the challenges of
data scarcity, we curate a comprehensive multi-human interaction dataset,
SocialX, enriched with textual annotations. Leveraging this dataset, we
establish the first comprehensive benchmark for multi-human interaction tasks.
Our method achieves state-of-the-art performance across motion-language tasks,
setting a new standard for multi-human interaction modeling.
