STARS: From Spatiotemporal Dynamics to Social Representations in Human-Robot Interaction
cs.RO, cs.LG
Submitted: 2026-09-30
Updated: 2026-10-06
Comments: Conference on Robot Learning (CoRL) 2026. First two authors contributed equally. Project site: https://larg.github.io/stars/
Project page: https://larg.github.io/stars
License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Terminology
Sources
- Social World Models
- Does Spatial Cognition Emerge in Frontier Models?
- Relational inductive biases, deep learning, and graph networks
- JRDB: A Dataset and Benchmark of Egocentric Robot Visual Perception of Humans in Built Environments
- Predicting Human Perceptions of Robot Performance During Navigation Tasks
- On the Opportunities and Risks of Foundation Models
- Mastering Diverse Domains through World Models
- OpenVLA: An Open-Source Vision-Language-Action Model
- NatSGD: A Dataset with Speech, Gestures, and Demonstrations for Robot Learning in Natural Human-Robot Interaction
- Learning Visual Dynamics Models of Rigid Objects using Relational Inductive Biases
- Variational Graph Auto-Encoders
- Heterogeneous Edge-Enhanced Graph Attention Network For Multi-Agent Trajectory Prediction
- Understanding intermediate layers using linear classifier probes
- Decoupled Weight Decay Regularization
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