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cs.AI2026
Coverage Aware Active Evaluation for Failure Discovery with Paired Systems
Anjali Parashar, Rachel Luo, Apoorva Sharma +6
Autonomous systems can fail in rare and heterogeneous ways, making real-world failure discovery difficult under limited testing budgets. Although cheaper proxies such as simulators…
cs.AI2026
Scenario Generation for Testing of Autonomous Driving Systems Using Real-World Failure Records
Anjali Parashar, Chuchu Fan
To ensure safe on-road behavior, pre-deployment testing and failure discovery of Autonomous Driving Systems (ADS) is crucial. Present day simulation based testing methods focus lar…
cs.AI2026
SEED-SET: Scalable Evolving Experimental Design for System-level Ethical Testing
Anjali Parashar, Yingke Li, Eric Yang Yu +4
As autonomous systems such as drones, become increasingly deployed in high-stakes, human-centric domains, it is critical to evaluate the ethical alignment since failure to do so im…