Search Results for author: Ziyuan Zhong

Found 10 papers, 7 papers with code

Language-Guided Traffic Simulation via Scene-Level Diffusion

no code implementations10 Jun 2023 Ziyuan Zhong, Davis Rempe, Yuxiao Chen, Boris Ivanovic, Yulong Cao, Danfei Xu, Marco Pavone, Baishakhi Ray

Realistic and controllable traffic simulation is a core capability that is necessary to accelerate autonomous vehicle (AV) development.

Language Modelling Large Language Model

Repairing Group-Level Errors for DNNs Using Weighted Regularization

1 code implementation24 Mar 2022 Ziyuan Zhong, Yuchi Tian, Conor J. Sweeney, Vicente Ordonez, Baishakhi Ray

In particular, it can repair confusion error and bias error of DNN models for both single-label and multi-label image classifications.

A Survey on Scenario-Based Testing for Automated Driving Systems in High-Fidelity Simulation

no code implementations2 Dec 2021 Ziyuan Zhong, Yun Tang, Yuan Zhou, Vania de Oliveira Neves, Yang Liu, Baishakhi Ray

To bridge this gap, in this work, we provide a generic formulation of scenario-based testing in high-fidelity simulation and conduct a literature review on the existing works.

Detecting Multi-Sensor Fusion Errors in Advanced Driver-Assistance Systems

3 code implementations14 Sep 2021 Ziyuan Zhong, Zhisheng Hu, Shengjian Guo, Xinyang Zhang, Zhenyu Zhong, Baishakhi Ray

We define the failures (e. g., car crashes) caused by the faulty MSF as fusion errors and develop a novel evolutionary-based domain-specific search framework, FusED, for the efficient detection of fusion errors.

Autonomous Driving Sensor Fusion

Neural Network Guided Evolutionary Fuzzing for Finding Traffic Violations of Autonomous Vehicles

1 code implementation13 Sep 2021 Ziyuan Zhong, Gail Kaiser, Baishakhi Ray

Self-driving cars and trucks, autonomous vehicles (AVs), should not be accepted by regulatory bodies and the public until they have much higher confidence in their safety and reliability -- which can most practically and convincingly be achieved by testing.

Self-Driving Cars

Understanding Local Robustness of Deep Neural Networks under Natural Variations

1 code implementation9 Oct 2020 Ziyuan Zhong, Yuchi Tian, Baishakhi Ray

To this end, we study the local per-input robustness properties of the DNNs and leverage those properties to build a white-box (DeepRobust-W) and a black-box (DeepRobust-B) tool to automatically identify the non-robust points.

Autonomous Driving Image Classification

Testing DNN Image Classifiers for Confusion & Bias Errors

1 code implementation20 May 2019 Yuchi Tian, Ziyuan Zhong, Vicente Ordonez, Gail Kaiser, Baishakhi Ray

We found that many of the reported erroneous cases in popular DNN image classifiers occur because the trained models confuse one class with another or show biases towards some classes over others.

Avg DNN Testing +3

Noise-tolerant fair classification

1 code implementation NeurIPS 2019 Alexandre Louis Lamy, Ziyuan Zhong, Aditya Krishna Menon, Nakul Verma

We finally show that our procedure is empirically effective on two case-studies involving sensitive feature censoring.

Classification Fairness +1

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