{"total":90,"rows":[{"id":"2405.14062","title":"ChatScene: Knowledge-Enabled Safety-Critical Scenario Generation for Autonomous Vehicles","created":"2024-05-22","cited_by_count":93,"area":"driving"},{"id":"2206.09682","title":"SafeBench: A Benchmarking Platform for Safety Evaluation of Autonomous Vehicles","created":"2022-06-20","cited_by_count":66,"area":"driving"},{"id":"2310.12432","title":"CAT: Closed-loop Adversarial Training for Safe End-to-End Driving","created":"2023-10-19","cited_by_count":54,"area":"driving"},{"id":"2209.08744","title":"AdvDO: Realistic Adversarial Attacks for Trajectory Prediction","created":"2022-09-19","cited_by_count":49,"area":null},{"id":"2304.12205","title":"Synthetic Datasets for Autonomous Driving: A Survey","created":"2023-04-24","cited_by_count":48,"area":null},{"id":"2303.16005","title":"Uncovering the Missing Pattern: Unified Framework Towards Trajectory Imputation and Prediction","created":"2023-03-28","cited_by_count":47,"area":null},{"id":"2302.14435","title":"ProxyFormer: Proxy Alignment Assisted Point Cloud Completion with Missing Part Sensitive Transformer","created":"2023-02-28","cited_by_count":43,"area":null},{"id":"2401.00391","title":"SAFE-SIM: Safety-Critical Closed-Loop Traffic Simulation with Diffusion-Controllable Adversaries","created":"2023-12-31","cited_by_count":38,"area":"diffusion"},{"id":"2211.00385","title":"Behavioral Intention Prediction in Driving Scenes: A Survey","created":"2022-11-01","cited_by_count":30,"area":null},{"id":"2410.08453","title":"AdvDiffuser: Generating Adversarial Safety-Critical Driving Scenarios via Guided Diffusion","created":"2024-10-11","cited_by_count":20,"area":"diffusion"},{"id":"2310.00633","title":"A Survey of Robustness and Safety of 2D and 3D Deep Learning Models Against Adversarial Attacks","created":"2023-10-01","cited_by_count":19,"area":null},{"id":"2207.03586","title":"CausalAgents: A Robustness Benchmark for Motion Forecasting using Causal Relationships","created":"2022-07-07","cited_by_count":18,"area":null},{"id":"2208.00094","title":"Robust Trajectory Prediction against Adversarial Attacks","created":"2022-07-29","cited_by_count":17,"area":null},{"id":"2304.08600","title":"RS2G: Data-Driven Scene-Graph Extraction and Embedding for Robust Autonomous Perception and Scenario Understanding","created":"2023-04-17","cited_by_count":17,"area":null},{"id":"2305.06292","title":"Joint Metrics Matter: A Better Standard for Trajectory Forecasting","created":"2023-05-10","cited_by_count":17,"area":null},{"id":"2208.09801","title":"PointDP: Diffusion-driven Purification against Adversarial Attacks on 3D Point Cloud Recognition","created":"2022-08-21","cited_by_count":16,"area":null},{"id":"2408.03200","title":"Adversarial Safety-Critical Scenario Generation using Naturalistic Human Driving Priors","created":"2024-08-06","cited_by_count":15,"area":"driving"},{"id":"2306.00349","title":"CALICO: Self-Supervised Camera-LiDAR Contrastive Pre-training for BEV Perception","created":"2023-06-01","cited_by_count":14,"area":null},{"id":"2409.09575","title":"Traffic Scene Generation from Natural Language Description for Autonomous Vehicles with Large Language Model","created":"2024-09-15","cited_by_count":14,"area":"driving"},{"id":"2205.14230","title":"Semi-supervised Semantics-guided Adversarial Training for Trajectory Prediction","created":"2022-05-27","cited_by_count":12,"area":null},{"id":"2212.04138","title":"Targeted Adversarial Attacks against Neural Network Trajectory Predictors","created":"2022-12-08","cited_by_count":11,"area":null},{"id":"2302.01060","title":"Physics Constrained Motion Prediction with Uncertainty Quantification","created":"2023-02-02","cited_by_count":11,"area":null},{"id":"2304.14614","title":"Fusion is Not Enough: Single Modal Attacks on Fusion Models for 3D Object Detection","created":"2023-04-28","cited_by_count":11,"area":null},{"id":"2309.12955","title":"On Data Fabrication in Collaborative Vehicular Perception: Attacks and Countermeasures","created":"2023-09-22","cited_by_count":11,"area":null},{"id":"2309.15251","title":"VPA: Fully Test-Time Visual Prompt Adaptation","created":"2023-09-26","cited_by_count":11,"area":null},{"id":"2409.18218","title":"Learning to Drive via Asymmetric Self-Play","created":"2024-09-26","cited_by_count":11,"area":"driving"},{"id":"2212.03806","title":"Towards Explainable Motion Prediction using Heterogeneous Graph Representations","created":"2022-12-07","cited_by_count":10,"area":null},{"id":"2311.01446","title":"Adv3D: Generating Safety-Critical 3D Objects through Closed-Loop Simulation","created":"2023-11-02","cited_by_count":10,"area":null},{"id":"2505.11247","title":"LD-Scene: LLM-Guided Diffusion for Controllable Generation of Adversarial Safety-Critical Driving Scenarios","created":"2025-05-16","cited_by_count":10,"area":"diffusion"},{"id":"2308.05985","title":"TrajPAC: Towards Robustness Verification of Pedestrian Trajectory Prediction Models","created":"2023-08-11","cited_by_count":8,"area":null},{"id":"2404.13425","title":"Enhancing Adversarial Robustness of Vision-Language Models through Low-Rank Adaptation","created":"2024-04-20","cited_by_count":8,"area":"mllm"},{"id":"2511.07292","title":"PlanT 2.0: Exposing Biases and Structural Flaws in Closed-Loop Driving","created":"2025-11-10","cited_by_count":8,"area":"driving"},{"id":"2503.05808","title":"DriveGen: Towards Infinite Diverse Traffic Scenarios with Large Models","created":"2025-03-04","cited_by_count":7,"area":null},{"id":"2303.05000","title":"Learning Representation for Anomaly Detection of Vehicle Trajectories","created":"2023-03-09","cited_by_count":6,"area":null},{"id":"2306.15755","title":"Adversarial Backdoor Attack by Naturalistic Data Poisoning on Trajectory Prediction in Autonomous Driving","created":"2023-06-27","cited_by_count":6,"area":null},{"id":"2312.03286","title":"Indirect Gradient Matching for Adversarial Robust Distillation","created":"2023-12-06","cited_by_count":6,"area":null},{"id":"2403.05770","title":"Towards Deviation-Robust Agent Navigation via Perturbation-Aware Contrastive Learning","created":"2024-03-09","cited_by_count":6,"area":null},{"id":"2403.13778","title":"Certified Human Trajectory Prediction","created":"2024-03-20","cited_by_count":6,"area":null},{"id":"2409.14488","title":"Enhancing LLM-based Autonomous Driving Agents to Mitigate Perception Attacks","created":"2024-09-22","cited_by_count":6,"area":"driving"},{"id":"2211.05455","title":"Benchmark for Models Predicting Human Behavior in Gap Acceptance Scenarios","created":"2022-11-10","cited_by_count":5,"area":null},{"id":"2309.15685","title":"Improving Autonomous Driving Safety with POP: A Framework for Accurate Partially Observed Trajectory Predictions","created":"2023-09-27","cited_by_count":5,"area":"driving"},{"id":"2503.06461","title":"Long-tailed Adversarial Training with Self-Distillation","created":"2025-03-09","cited_by_count":5,"area":"distill"},{"id":"2507.13729","title":"AGENTS-LLM: Augmentative GENeration of Challenging Traffic Scenarios with an Agentic LLM Framework","created":"2025-07-18","cited_by_count":5,"area":"agents"},{"id":"2508.14527","title":"Adversarial Generation and Collaborative Evolution of Safety-Critical Scenarios for Autonomous Vehicles","created":"2025-08-20","cited_by_count":5,"area":"driving"},{"id":"2303.04340","title":"Privacy-preserving and Uncertainty-aware Federated Trajectory Prediction for Connected Autonomous Vehicles","created":"2023-03-08","cited_by_count":4,"area":null},{"id":"2402.18393","title":"Decictor: Towards Evaluating the Robustness of Decision-Making in Autonomous Driving Systems","created":"2024-02-28","cited_by_count":4,"area":null},{"id":"2409.07321","title":"Module-wise Adaptive Adversarial Training for End-to-end Autonomous Driving","created":"2024-09-11","cited_by_count":4,"area":"driving"},{"id":"2509.16950","title":"Temporal Logic-Based Multi-Vehicle Backdoor Attacks against Offline RL Agents in End-to-end Autonomous Driving","created":"2025-09-21","cited_by_count":4,"area":"safety"},{"id":"2406.11707","title":"A First Physical-World Trajectory Prediction Attack via LiDAR-induced Deceptions in Autonomous Driving","created":"2024-06-17","cited_by_count":3,"area":null},{"id":"2407.18756","title":"Evaluating Human Trajectory Prediction with Metamorphic Testing","created":"2024-07-26","cited_by_count":3,"area":null},{"id":"2408.10647","title":"Privacy-preserving Universal Adversarial Defense for Black-box Models","created":"2024-08-20","cited_by_count":3,"area":null},{"id":"2409.17277","title":"Building Real-time Awareness of Out-of-distribution in Trajectory Prediction for Autonomous Vehicles","created":"2024-09-25","cited_by_count":3,"area":null},{"id":"2411.17376","title":"RealTraj: Towards Real-World Pedestrian Trajectory Forecasting","created":"2024-11-26","cited_by_count":3,"area":null},{"id":"2505.06134","title":"Realistic Adversarial Attacks for Robustness Evaluation of Trajectory Prediction Models via Future State Perturbation","created":"2025-05-09","cited_by_count":3,"area":null},{"id":"2603.15221","title":"ADV-0: Closed-Loop Min-Max Adversarial Training for Long-Tail Robustness in Autonomous Driving","created":"2026-03-16","cited_by_count":3,"area":"driving"},{"id":"2605.21446","title":"Lost in Fog: Sensor Perturbations Expose Reasoning Fragility in Driving VLAs","created":"2026-05-20","cited_by_count":3,"area":"driving"},{"id":"2404.16579","title":"Neural Interaction Energy for Multi-Agent Trajectory Prediction","created":"2024-04-25","cited_by_count":2,"area":null},{"id":"2407.04359","title":"Dance of the ADS: Orchestrating Failures through Historically-Informed Scenario Fuzzing","created":"2024-07-05","cited_by_count":2,"area":null},{"id":"2411.10500","title":"Edge-Only Universal Adversarial Attacks in Distributed Learning","created":"2024-11-15","cited_by_count":2,"area":null},{"id":"2503.20654","title":"AccidentSim: Generating Vehicle Collision Videos with Physically Realistic Collision Trajectories from Real-World Accident Reports","created":"2025-03-26","cited_by_count":2,"area":"wm"},{"id":"2509.14801","title":"STEP: Structured Training and Evaluation Platform for benchmarking trajectory prediction models","created":"2025-09-18","cited_by_count":2,"area":null},{"id":"2512.01934","title":"Physical ID-Transfer Attacks against Multi-Object Tracking via Adversarial Trajectory","created":"2025-12-01","cited_by_count":2,"area":null},{"id":"2304.01895","title":"Robustness Benchmark of Road User Trajectory Prediction Models for Automated Driving","created":"2023-04-04","cited_by_count":1,"area":null},{"id":"2305.19194","title":"FakeSwarm: Improving Fake News Detection with Swarming Characteristics","created":"2023-05-30","cited_by_count":1,"area":null},{"id":"2311.07880","title":"VegaEdge: Edge AI Confluence Anomaly Detection for Real-Time Highway IoT-Applications","created":"2023-11-14","cited_by_count":1,"area":null},{"id":"2404.12612","title":"SA-Attack: Speed-adaptive stealthy adversarial attack on trajectory prediction","created":"2024-04-19","cited_by_count":1,"area":null},{"id":"2503.23708","title":"Towards Benchmarking and Assessing the Safety and Robustness of Autonomous Driving on Safety-critical Scenarios","created":"2025-03-31","cited_by_count":1,"area":"driving"},{"id":"2504.08414","title":"Adversarial Examples in Environment Perception for Automated Driving (Review)","created":"2025-04-11","cited_by_count":1,"area":null},{"id":"2504.17966","title":"Plug-and-Play Physics-informed Learning using Uncertainty Quantified Port-Hamiltonian Models","created":"2025-04-24","cited_by_count":1,"area":null},{"id":"2506.11472","title":"Toward Inherently Robust VLMs Against Visual Perception Attacks","created":"2025-06-13","cited_by_count":1,"area":"mllm"},{"id":"2508.17265","title":"AdaGAT: Adaptive Guidance Adversarial Training for the Robustness of Deep Neural Networks","created":"2025-08-24","cited_by_count":1,"area":"distill"},{"id":"2603.10821","title":"Evaluating randomized smoothing as a defense against adversarial attacks in trajectory prediction","created":"2026-03-11","cited_by_count":1,"area":null},{"id":"2312.13863","title":"Manipulating Trajectory Prediction with Backdoors","created":"2023-12-21","cited_by_count":0,"area":null},{"id":"2401.10313","title":"Hacking Predictors Means Hacking Cars: Using Sensitivity Analysis to Identify Trajectory Prediction Vulnerabilities for Autonomous Driving Security","created":"2024-01-18","cited_by_count":0,"area":"driving"},{"id":"2403.05666","title":"Prepared for the Worst: A Learning-Based Adversarial Attack for Resilience Analysis of the ICP Algorithm","created":"2024-03-08","cited_by_count":0,"area":null},{"id":"2409.15224","title":"Enhancing Pedestrian Trajectory Prediction with Crowd Trip Information","created":"2024-09-23","cited_by_count":0,"area":null},{"id":"2509.13577","title":"Adaptive Multi-Mode Out-of-Distribution Detection for Trajectory Prediction in Autonomous Vehicles","created":"2025-09-16","cited_by_count":0,"area":"driving"},{"id":"2512.10275","title":"Sample-wise Adaptive Weighting for Transfer Consistency in Adversarial Distillation","created":"2025-12-11","cited_by_count":0,"area":null},{"id":"2601.01109","title":"NADD: Amplifying Noise for Effective Diffusion-based Adversarial Purification","created":"2026-01-03","cited_by_count":0,"area":"diffusion"},{"id":"2602.16236","title":"Online Prediction of Stochastic Sequences with High Probability Regret Bounds","created":"2026-02-18","cited_by_count":0,"area":null},{"id":"2604.03463","title":"Super Agents and Confounders: Influence of surrounding agents on vehicle trajectory prediction","created":"2026-04-03","cited_by_count":0,"area":null},{"id":"2604.12408","title":"Security and Resilience in Autonomous Vehicles: A Proactive Design Approach","created":"2026-04-14","cited_by_count":0,"area":null},{"id":"2605.06087","title":"Safety Certification is Classification","created":"2026-05-07","cited_by_count":0,"area":null},{"id":"2605.12743","title":"Still Camouflage, Moving Illusion: View-Induced Trajectory Manipulation in Autonomous Driving","created":"2026-05-12","cited_by_count":0,"area":"driving"},{"id":"2605.18895","title":"KG-ASG: Collision-Knowledge-Guided Closed-Loop Adversarial Scenario Generation With Primary-Support Attribution","created":"2026-05-17","cited_by_count":0,"area":null},{"id":"2605.21168","title":"ScenePilot: Controllable Boundary-Driven Critical Scenario Generation for Autonomous Driving","created":"2026-05-20","cited_by_count":0,"area":"driving"},{"id":"2606.03678","title":"EvoDrive: Pareto Evolution for Safety-Critical Autonomous Driving via Self-Improving LLM Agents","created":"2026-06-02","cited_by_count":0,"area":"agents"},{"id":"2606.28716","title":"TrajRS: Towards Certified Robustness in Pedestrian Trajectory Prediction","created":"2026-06-27","cited_by_count":0,"area":null},{"id":"2606.29097","title":"TrafficAlign: Aligning Large Language Models for Traffic Scenario Generation","created":"2026-06-27","cited_by_count":0,"area":"alignment"},{"id":"2609.29600","title":"Active Client Selection in Federated Trajectory Prediction with Uncertainty-Awareness and Heterogeneous Complexity","created":"2026-08-27","cited_by_count":0,"area":null}],"next_cursor":null}