ScenGE generates more collision-prone autonomous driving test scenarios by combining LLM-suggested adversarial events with optimized background traffic, beating prior generators on CARLA benchmarks.
A survey on in-context learning
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
citation-role summary
background 1
citation-polarity summary
fields
cs.CV 1years
2025 1verdicts
CONDITIONAL 1roles
background 1polarities
unclear 1representative citing papers
citing papers explorer
-
Adversarial Generation and Collaborative Evolution of Safety-Critical Scenarios for Autonomous Vehicles
ScenGE generates more collision-prone autonomous driving test scenarios by combining LLM-suggested adversarial events with optimized background traffic, beating prior generators on CARLA benchmarks.