Search Results for author: Xiaofei Xie

Found 47 papers, 12 papers with code

Bias Assessment and Mitigation in LLM-based Code Generation

no code implementations3 Sep 2023 Dong Huang, Qingwen Bu, Jie Zhang, Xiaofei Xie, Junjie Chen, Heming Cui

Utilizing state-of-the-art Large Language Models (LLMs), automatic code generation models play a pivotal role in enhancing the productivity and efficiency of software development coding procedures.

Code Generation Fairness

When GPT Meets Program Analysis: Towards Intelligent Detection of Smart Contract Logic Vulnerabilities in GPTScan

no code implementations7 Aug 2023 Yuqiang Sun, Daoyuan Wu, Yue Xue, Han Liu, Haijun Wang, Zhengzi Xu, Xiaofei Xie, Yang Liu

Instead of relying solely on GPT to identify vulnerabilities, which can lead to high false positives and is limited by GPT's pre-trained knowledge, we utilize GPT as a versatile code understanding tool.

Vulnerability Detection

Evaluating the Robustness of Test Selection Methods for Deep Neural Networks

no code implementations29 Jul 2023 Qiang Hu, Yuejun Guo, Xiaofei Xie, Maxime Cordy, Wei Ma, Mike Papadakis, Yves Le Traon

Testing deep learning-based systems is crucial but challenging due to the required time and labor for labeling collected raw data.

Fault Detection

Multi-target Backdoor Attacks for Code Pre-trained Models

no code implementations14 Jun 2023 Yanzhou Li, Shangqing Liu, Kangjie Chen, Xiaofei Xie, Tianwei Zhang, Yang Liu

We evaluate our approach on two code understanding tasks and three code generation tasks over seven datasets.

Code Generation Representation Learning

Evading DeepFake Detectors via Adversarial Statistical Consistency

no code implementations CVPR 2023 Yang Hou, Qing Guo, Yihao Huang, Xiaofei Xie, Lei Ma, Jianjun Zhao

Second, we find that the statistical differences between natural and DeepFake images are positively associated with the distribution shifting between the two kinds of images, and we propose to use a distribution-aware loss to guide the optimization of different degradations.

DeepFake Detection Face Swapping

Neural Episodic Control with State Abstraction

no code implementations27 Jan 2023 Zhuo Li, Derui Zhu, Yujing Hu, Xiaofei Xie, Lei Ma, Yan Zheng, Yan Song, Yingfeng Chen, Jianjun Zhao

Generally, episodic control-based approaches are solutions that leverage highly-rewarded past experiences to improve sample efficiency of DRL algorithms.

OpenAI Gym

Are Code Pre-trained Models Powerful to Learn Code Syntax and Semantics?

no code implementations20 Dec 2022 Wei Ma, Mengjie Zhao, Xiaofei Xie, Qiang Hu, Shangqing Liu, Jie Zhang, Wenhan Wang, Yang Liu

To further understand the code features learnt by these models, in this paper, we target two well-known representative code pre-trained models (i. e., CodeBERT and GraphCodeBERT) and devise a set of probing tasks for the syntax and semantics analysis.

Code Completion Code Search +2

Decompiling x86 Deep Neural Network Executables

no code implementations3 Oct 2022 Zhibo Liu, Yuanyuan Yuan, Shuai Wang, Xiaofei Xie, Lei Ma

BTD takes DNN executables and outputs full model specifications, including types of DNN operators, network topology, dimensions, and parameters that are (nearly) identical to those of the input models.

CommitBART: A Large Pre-trained Model for GitHub Commits

no code implementations17 Aug 2022 Shangqing Liu, Yanzhou Li, Xiaofei Xie, Yang Liu

GitHub commits, which record the code changes with natural language messages for description, play a critical role for software developers to comprehend the software evolution.

Contrastive Learning Denoising

Aries: Efficient Testing of Deep Neural Networks via Labeling-Free Accuracy Estimation

1 code implementation22 Jul 2022 Qiang Hu, Yuejun Guo, Xiaofei Xie, Maxime Cordy, Lei Ma, Mike Papadakis, Yves Le Traon

Recent studies show that test selection for DNN is a promising direction that tackles this issue by selecting minimal representative data to label and using these data to assess the model.

CodeS: Towards Code Model Generalization Under Distribution Shift

no code implementations11 Jun 2022 Qiang Hu, Yuejun Guo, Xiaofei Xie, Maxime Cordy, Lei Ma, Mike Papadakis, Yves Le Traon

Distribution shift has been a longstanding challenge for the reliable deployment of deep learning (DL) models due to unexpected accuracy degradation.

Benchmarking Code Classification

LaF: Labeling-Free Model Selection for Automated Deep Neural Network Reusing

1 code implementation8 Apr 2022 Qiang Hu, Yuejun Guo, Maxime Cordy, Xiaofei Xie, Mike Papadakis, Yves Le Traon

Applying deep learning to science is a new trend in recent years which leads DL engineering to become an important problem.

Model Selection

NPC: Neuron Path Coverage via Characterizing Decision Logic of Deep Neural Networks

no code implementations24 Mar 2022 Xiaofei Xie, Tianlin Li, Jian Wang, Lei Ma, Qing Guo, Felix Juefei-Xu, Yang Liu

Inspired by software testing, a number of structural coverage criteria are designed and proposed to measure the test adequacy of DNNs.

Defect Detection DNN Testing +1

Learning Program Semantics with Code Representations: An Empirical Study

1 code implementation22 Mar 2022 Jing Kai Siow, Shangqing Liu, Xiaofei Xie, Guozhu Meng, Yang Liu

However, currently, a comprehensive and systematic study on evaluating different program representation techniques across diverse tasks is still missed.

Clone Detection Code Classification +1

Unveiling Project-Specific Bias in Neural Code Models

no code implementations19 Jan 2022 Zhiming Li, Yanzhou Li, Tianlin Li, Mengnan Du, Bozhi Wu, Yushi Cao, Xiaofei Xie, Yi Li, Yang Liu

Neural code models have introduced significant improvements over many software analysis tasks like type inference, vulnerability detection, etc.

Adversarial Robustness Vulnerability Detection

GraphSearchNet: Enhancing GNNs via Capturing Global Dependencies for Semantic Code Search

1 code implementation4 Nov 2021 Shangqing Liu, Xiaofei Xie, JingKai Siow, Lei Ma, Guozhu Meng, Yang Liu

Specifically, we propose to construct graphs for the source code and queries with bidirectional GGNN (BiGGNN) to capture the local structural information of the source code and queries.

Code Search Code Summarization +3

Learning to Adversarially Blur Visual Object Tracking

1 code implementation ICCV 2021 Qing Guo, Ziyi Cheng, Felix Juefei-Xu, Lei Ma, Xiaofei Xie, Yang Liu, Jianjun Zhao

In this work, we explore the robustness of visual object trackers against motion blur from a new angle, i. e., adversarial blur attack (ABA).

Visual Object Tracking Visual Tracking

Cross-Lingual Transfer Learning for Statistical Type Inference

no code implementations1 Jul 2021 Zhiming Li, Xiaofei Xie, Haoliang Li, Zhengzi Xu, Yi Li, Yang Liu

Hitherto statistical type inference systems rely thoroughly on supervised learning approaches, which require laborious manual effort to collect and label large amounts of data.

Code Summarization Cross-Lingual Transfer +4

AVA: Adversarial Vignetting Attack against Visual Recognition

no code implementations12 May 2021 Binyu Tian, Felix Juefei-Xu, Qing Guo, Xiaofei Xie, Xiaohong Li, Yang Liu

Moreover, we propose the geometry-aware level-set optimization method to solve the adversarial vignetting regions and physical parameters jointly.

Independent Reinforcement Learning for Weakly Cooperative Multiagent Traffic Control Problem

1 code implementation22 Apr 2021 Chengwei Zhang, Shan Jin, Wanli Xue, Xiaofei Xie, ShengYong Chen, Rong Chen

To this, we model the traffic control problem as a partially observable weak cooperative traffic model (PO-WCTM) to optimize the overall traffic situation of a group of intersections.

Decision Making reinforcement-learning +1

Neuron Coverage-Guided Domain Generalization

no code implementations27 Feb 2021 Chris Xing Tian, Haoliang Li, Xiaofei Xie, Yang Liu, Shiqi Wang

More specifically, by treating the DNN as a program and each neuron as a functional point of the code, during the network training we aim to improve the generalization capability by maximizing the neuron coverage of DNN with the gradient similarity regularization between the original and augmented samples.

DNN Testing Domain Generalization

Sparta: Spatially Attentive and Adversarially Robust Activations

no code implementations1 Jan 2021 Qing Guo, Felix Juefei-Xu, Changqing Zhou, Lei Ma, Xiaofei Xie, Wei Feng, Yang Liu

Moreover, comprehensive evaluations have demonstrated two important properties of our method: First, superior transferability across DNNs.


EfficientDeRain: Learning Pixel-wise Dilation Filtering for High-Efficiency Single-Image Deraining

2 code implementations19 Sep 2020 Qing Guo, Jingyang Sun, Felix Juefei-Xu, Lei Ma, Xiaofei Xie, Wei Feng, Yang Liu

To fill this gap, in this paper, we regard the single-image deraining as a general image-enhancing problem and originally propose a model-free deraining method, i. e., EfficientDeRain, which is able to process a rainy image within 10~ms (i. e., around 6~ms on average), over 80 times faster than the state-of-the-art method (i. e., RCDNet), while achieving similar de-rain effects.

Data Augmentation Single Image Deraining

Bias Field Poses a Threat to DNN-based X-Ray Recognition

no code implementations19 Sep 2020 Binyu Tian, Qing Guo, Felix Juefei-Xu, Wen Le Chan, Yupeng Cheng, Xiaohong Li, Xiaofei Xie, Shengchao Qin

Our method reveals the potential threat to the DNN-based X-ray automated diagnosis and can definitely benefit the development of bias-field-robust automated diagnosis system.

Adversarial Attack

Adversarial Rain Attack and Defensive Deraining for DNN Perception

no code implementations19 Sep 2020 Liming Zhai, Felix Juefei-Xu, Qing Guo, Xiaofei Xie, Lei Ma, Wei Feng, Shengchao Qin, Yang Liu

To defend the DNNs from the negative rain effect, we also present a defensive deraining strategy, for which we design an adversarial rain augmentation that uses mixed adversarial rain layers to enhance deraining models for downstream DNN perception.

Adversarial Attack Autonomous Driving +5

Adversarial Exposure Attack on Diabetic Retinopathy Imagery

no code implementations19 Sep 2020 Yupeng Cheng, Felix Juefei-Xu, Qing Guo, Huazhu Fu, Xiaofei Xie, Shang-Wei Lin, Weisi Lin, Yang Liu

In this paper, we study this problem from the viewpoint of adversarial attack and identify a totally new task, i. e., adversarial exposure attack generating adversarial images by tuning image exposure to mislead the DNNs with significantly high transferability.

Adversarial Attack

Light Can Hack Your Face! Black-box Backdoor Attack on Face Recognition Systems

no code implementations15 Sep 2020 Haoliang Li, Yufei Wang, Xiaofei Xie, Yang Liu, Shiqi Wang, Renjie Wan, Lap-Pui Chau, Alex C. Kot

In this paper, we propose a novel black-box backdoor attack technique on face recognition systems, which can be conducted without the knowledge of the targeted DNN model.

Backdoor Attack Face Recognition

Can We Trust Your Explanations? Sanity Checks for Interpreters in Android Malware Analysis

no code implementations13 Aug 2020 Ming Fan, Wenying Wei, Xiaofei Xie, Yang Liu, Xiaohong Guan, Ting Liu

For this reason, a variety of explanation approaches are proposed to interpret predictions by providing important features.

Cryptography and Security Software Engineering

DeepRhythm: Exposing DeepFakes with Attentional Visual Heartbeat Rhythms

no code implementations13 Jun 2020 Hua Qi, Qing Guo, Felix Juefei-Xu, Xiaofei Xie, Lei Ma, Wei Feng, Yang Liu, Jianjun Zhao

As the GAN-based face image and video generation techniques, widely known as DeepFakes, have become more and more matured and realistic, there comes a pressing and urgent demand for effective DeepFakes detectors.

DeepFake Detection Face Swapping +2

FakePolisher: Making DeepFakes More Detection-Evasive by Shallow Reconstruction

1 code implementation13 Jun 2020 Yihao Huang, Felix Juefei-Xu, Run Wang, Qing Guo, Lei Ma, Xiaofei Xie, Jianwen Li, Weikai Miao, Yang Liu, Geguang Pu

At this moment, GAN-based image generation methods are still imperfect, whose upsampling design has limitations in leaving some certain artifact patterns in the synthesized image.

DeepFake Detection Face Swapping +2

Retrieval-Augmented Generation for Code Summarization via Hybrid GNN

1 code implementation ICLR 2021 Shangqing Liu, Yu Chen, Xiaofei Xie, JingKai Siow, Yang Liu

However, automatic code summarization is challenging due to the complexity of the source code and the language gap between the source code and natural language summaries.

Code Summarization Retrieval +1

Stealing Deep Reinforcement Learning Models for Fun and Profit

no code implementations9 Jun 2020 Kangjie Chen, Shangwei Guo, Tianwei Zhang, Xiaofei Xie, Yang Liu

This paper presents the first model extraction attack against Deep Reinforcement Learning (DRL), which enables an external adversary to precisely recover a black-box DRL model only from its interaction with the environment.

Imitation Learning Model extraction +2

Stealthy and Efficient Adversarial Attacks against Deep Reinforcement Learning

no code implementations14 May 2020 Jianwen Sun, Tianwei Zhang, Xiaofei Xie, Lei Ma, Yan Zheng, Kangjie Chen, Yang Liu

Adversarial attacks against conventional Deep Learning (DL) systems and algorithms have been widely studied, and various defenses were proposed.

Adversarial Attack reinforcement-learning +1

Towards Characterizing Adversarial Defects of Deep Learning Software from the Lens of Uncertainty

no code implementations24 Apr 2020 Xiyue Zhang, Xiaofei Xie, Lei Ma, Xiaoning Du, Qiang Hu, Yang Liu, Jianjun Zhao, Meng Sun

Based on this, we propose an automated testing technique to generate multiple types of uncommon AEs and BEs that are largely missed by existing techniques.

Adversarial Attack

Byzantine-resilient Decentralized Stochastic Gradient Descent

no code implementations20 Feb 2020 Shangwei Guo, Tianwei Zhang, Han Yu, Xiaofei Xie, Lei Ma, Tao Xiang, Yang Liu

It guarantees that each benign node in a decentralized system can train a correct model under very strong Byzantine attacks with an arbitrary number of faulty nodes.

Edge-computing Image Classification

Amora: Black-box Adversarial Morphing Attack

no code implementations9 Dec 2019 Run Wang, Felix Juefei-Xu, Qing Guo, Yihao Huang, Xiaofei Xie, Lei Ma, Yang Liu

In this paper, we investigate and introduce a new type of adversarial attack to evade FR systems by manipulating facial content, called \textbf{\underline{a}dversarial \underline{mor}phing \underline{a}ttack} (a. k. a.

Adversarial Attack Dictionary Learning +3

SPARK: Spatial-aware Online Incremental Attack Against Visual Tracking

1 code implementation ECCV 2020 Qing Guo, Xiaofei Xie, Felix Juefei-Xu, Lei Ma, Zhongguo Li, Wanli Xue, Wei Feng, Yang Liu

We identify that online object tracking poses two new challenges: 1) it is difficult to generate imperceptible perturbations that can transfer across frames, and 2) real-time trackers require the attack to satisfy a certain level of efficiency.

Adversarial Attack Video Object Tracking +2

An Empirical Study towards Characterizing Deep Learning Development and Deployment across Different Frameworks and Platforms

no code implementations15 Sep 2019 Qianyu Guo, Sen Chen, Xiaofei Xie, Lei Ma, Qiang Hu, Hongtao Liu, Yang Liu, Jianjun Zhao, Xiaohong Li

However, the differences in architecture designs and implementations of existing frameworks and platforms bring new challenges for DL software development and deployment.

Adversarial Attack Adversarial Robustness +1

FakeSpotter: A Simple yet Robust Baseline for Spotting AI-Synthesized Fake Faces

no code implementations13 Sep 2019 Run Wang, Felix Juefei-Xu, Lei Ma, Xiaofei Xie, Yihao Huang, Jian Wang, Yang Liu

In recent years, generative adversarial networks (GANs) and its variants have achieved unprecedented success in image synthesis.

Face Detection Face Recognition +2

DeepCruiser: Automated Guided Testing for Stateful Deep Learning Systems

no code implementations13 Dec 2018 Xiaoning Du, Xiaofei Xie, Yi Li, Lei Ma, Jianjun Zhao, Yang Liu

Our in-depth evaluation on a state-of-the-art speech-to-text DL system demonstrates the effectiveness of our technique in improving quality and reliability of stateful DL systems.

An Orchestrated Empirical Study on Deep Learning Frameworks and Platforms

no code implementations13 Nov 2018 Qianyu Guo, Xiaofei Xie, Lei Ma, Qiang Hu, Ruitao Feng, Li Li, Yang Liu, Jianjun Zhao, Xiaohong Li

Up to the present, it still lacks a comprehensive study on how current diverse DL frameworks and platforms influence the DL software development process.

Autonomous Driving

Metamorphic Relation Based Adversarial Attacks on Differentiable Neural Computer

no code implementations7 Sep 2018 Alvin Chan, Lei Ma, Felix Juefei-Xu, Xiaofei Xie, Yang Liu, Yew Soon Ong

Deep neural networks (DNN), while becoming the driving force of many novel technology and achieving tremendous success in many cutting-edge applications, are still vulnerable to adversarial attacks.

Question Answering

DeepHunter: Hunting Deep Neural Network Defects via Coverage-Guided Fuzzing

no code implementations4 Sep 2018 Xiaofei Xie, Lei Ma, Felix Juefei-Xu, Hongxu Chen, Minhui Xue, Bo Li, Yang Liu, Jianjun Zhao, Jianxiong Yin, Simon See

In company with the data explosion over the past decade, deep neural network (DNN) based software has experienced unprecedented leap and is becoming the key driving force of many novel industrial applications, including many safety-critical scenarios such as autonomous driving.

Autonomous Driving Quantization

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