{"total":40,"rows":[{"id":"2101.05307","title":"Explainability of deep vision-based autonomous driving systems: Review and challenges","created":"2021-01-13","cited_by_count":80,"area":null},{"id":"2210.15432","title":"Many-Objective Reinforcement Learning for Online Testing of DNN-Enabled Systems","created":"2022-10-27","cited_by_count":19,"area":null},{"id":"2110.08664","title":"Finding Critical Scenarios for Automated Driving Systems: A Systematic Literature Review","created":"2021-10-16","cited_by_count":12,"area":null},{"id":"2112.02807","title":"MDPFuzz: Testing Models Solving Markov Decision Processes","created":"2021-12-06","cited_by_count":12,"area":null},{"id":"2109.06404","title":"Detecting Multi-Sensor Fusion Errors in Advanced Driver-Assistance Systems","created":"2021-09-14","cited_by_count":8,"area":null},{"id":"2107.12940","title":"Finding Failures in High-Fidelity Simulation using Adaptive Stress Testing and the Backward Algorithm","created":"2021-07-27","cited_by_count":7,"area":null},{"id":"2111.09884","title":"Assisted Robust Reward Design","created":"2021-11-18","cited_by_count":5,"area":null},{"id":"2505.21743","title":"Simulating the Unseen: Crash Prediction Must Learn from What Did Not Happen","created":"2025-05-27","cited_by_count":5,"area":null},{"id":"2304.00365","title":"Adaptive Failure Search Using Critical States from Domain Experts","created":"2023-04-01","cited_by_count":4,"area":null},{"id":"2111.02204","title":"Certifiable Deep Importance Sampling for Rare-Event Simulation of Black-Box Systems","created":"2021-11-03","cited_by_count":3,"area":null},{"id":"2112.00206","title":"Querying Labelled Data with Scenario Programs for Sim-to-Real Validation","created":"2021-12-01","cited_by_count":3,"area":null},{"id":"2202.03651","title":"Causal Scene BERT: Improving object detection by searching for challenging groups of data","created":"2022-02-08","cited_by_count":3,"area":null},{"id":"2305.09930","title":"Model-based Validation as Probabilistic Inference","created":"2023-05-17","cited_by_count":3,"area":null},{"id":"2411.17826","title":"Rate-Informed Discovery via Bayesian Adaptive Multifidelity Sampling","created":"2024-11-26","cited_by_count":3,"area":null},{"id":"2107.03577","title":"Adaptive Stress Testing for Adversarial Learning in a Financial Environment","created":"2021-07-08","cited_by_count":2,"area":null},{"id":"2211.12470","title":"A Deep Reinforcement Learning Approach to Rare Event Estimation","created":"2022-11-22","cited_by_count":2,"area":null},{"id":"2412.06684","title":"Exploring Critical Testing Scenarios for Decision-Making Policies: An LLM Approach","created":"2024-12-09","cited_by_count":2,"area":null},{"id":"2505.03178","title":"RADE: Learning Risk-Adjustable Driving Environment via Multi-Agent Conditional Diffusion","created":"2025-05-06","cited_by_count":2,"area":null},{"id":"2511.02164","title":"ScenicProver: A Framework for Compositional Probabilistic Verification of Learning-Enabled Systems","created":"2025-11-04","cited_by_count":2,"area":null},{"id":"2607.20532","title":"Position: Stop Reactively Patching Your Model Every Time and Start Proactive Test-Driven AI Development","created":"2026-07-10","cited_by_count":2,"area":null},{"id":"2204.02351","title":"Test Against High-Dimensional Uncertainties: Accelerated Evaluation of Autonomous Vehicles with Deep Importance Sampling","created":"2022-04-04","cited_by_count":1,"area":null},{"id":"2210.02168","title":"An Active Learning Reliability Method for Systems with Partially Defined Performance Functions","created":"2022-10-05","cited_by_count":1,"area":null},{"id":"2311.12722","title":"Attacking Motion Planners Using Adversarial Perception Errors","created":"2023-11-21","cited_by_count":1,"area":null},{"id":"2312.09559","title":"STEAM & MoSAFE: SOTIF Error-and-Failure Model & Analysis for AI-Enabled Driving Automation","created":"2023-12-15","cited_by_count":1,"area":null},{"id":"2412.00517","title":"LAMBDA: Covering the Multimodal Critical Scenarios for Automated Driving Systems by Search Space Quantization","created":"2024-11-30","cited_by_count":1,"area":null},{"id":"2104.00859","title":"An NCAP-like Safety Indicator for Self-Driving Cars","created":"2021-04-02","cited_by_count":0,"area":null},{"id":"2212.03530","title":"Curiosity creates Diversity in Policy Search","created":"2022-12-07","cited_by_count":0,"area":null},{"id":"2304.00367","title":"Conveying Autonomous Robot Capabilities through Contrasting Behaviour Summaries","created":"2023-04-01","cited_by_count":0,"area":null},{"id":"2308.14550","title":"ReMAV: Reward Modeling of Autonomous Vehicles for Finding Likely Failure Events","created":"2023-08-28","cited_by_count":0,"area":null},{"id":"2309.12474","title":"SAVME: Efficient Safety Validation for Autonomous Systems Using Meta-Learning","created":"2023-09-21","cited_by_count":0,"area":null},{"id":"2411.03328","title":"Foundation Models for Rapid Autonomy Validation","created":"2024-10-22","cited_by_count":0,"area":null},{"id":"2604.12857","title":"Artificial Intelligence for Modeling and Simulation of Mixed Automated and Human Traffic","created":"2026-04-14","cited_by_count":0,"area":null},{"id":"2604.20910","title":"Planetary Exploration 3.0: A Roadmap for Software-Defined, Radically Adaptive Space Systems","created":"2026-04-22","cited_by_count":0,"area":null},{"id":"2606.31131","title":"Scenario Generation for Testing of Autonomous Driving Systems Using Real-World Failure Records","created":"2026-06-30","cited_by_count":0,"area":null},{"id":"2607.04451","title":"CCFM: Collision-Constrained Flow Matching for Safety-Critical Scenario Generation","created":"2026-07-05","cited_by_count":0,"area":null},{"id":"2607.18637","title":"End-to-end Conditional Diffusion for Realistic and Controllable Visual Traffic Scenario Generation","created":"2026-07-21","cited_by_count":0,"area":null},{"id":"2607.26121","title":"Towards Trustworthy Embodied Intelligence: A Systems Framework and Graded Trustworthiness Levels","created":"2026-07-28","cited_by_count":0,"area":null},{"id":"2608.09622","title":"Adaptive Sequential Test Planning for Multi-Mechanism Reliability Qualification via Bayesian Monte Carlo Tree Search","created":"2026-08-10","cited_by_count":0,"area":null},{"id":"2609.06433","title":"Collision Snapshot Guided Time-Reversed Safety-Critical Scenario Generation","created":"2026-09-06","cited_by_count":0,"area":null},{"id":"2610.05003","title":"How corner is a corner case? Percentile control for highway scenario generation","created":"2026-10-04","cited_by_count":0,"area":null}],"next_cursor":null}