In this work, we propose InteractTraj, the first language-driven traffic trajectory generator that can generate interactive traffic trajectories.

When such components are expected to be embedded in safety-critical systems (e.g.,

How (dis)similar are the learning trajectories of vision-language models and children? Recent modeling work has attempted to understand the gap between models'

LLMs excel at few-shot in-context learning (ICL) - learning from a few input-output examples ("shots") provided in context at inference, without any weight updates.