Real World Interaction

Real-world interaction research focuses on understanding and modeling how humans and artificial agents (like LLMs and robots) interact in diverse, unconstrained settings. Current efforts concentrate on developing benchmarks and datasets capturing these interactions, often using generative models to create realistic synthetic data or analyzing large-scale human-AI dialogue logs. This research is crucial for improving the safety, reliability, and social competence of AI systems, as well as for developing more accurate and consistent tools for applications like healthcare assessments and educational technologies.