AutoSceneGen uses LLM in-context learning to generate CARLA traffic scenarios and trains trajectory predictors on the synthetic data, but its claimed improvements are inconsistent and unsupported.
Title resolution pending
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.RO 1years
2024 1verdicts
REJECT 1representative citing papers
citing papers explorer
-
Generating Traffic Scenarios via In-Context Learning to Learn Better Motion Planner
AutoSceneGen uses LLM in-context learning to generate CARLA traffic scenarios and trains trajectory predictors on the synthetic data, but its claimed improvements are inconsistent and unsupported.