526互联

understanding pre-trained generation cdeepfuzz

Understanding UML in seconds

UML 是一种分析设计语言，也就是一种建模语言。 UML结构解析 UML其结构主要包括以下几个部分： 视图（View） 多个图形组成的集合； 图（Diagram） 图的种类有13种图，但常用的也就两种（1.需求用例图，2.开发类图）； 模型元素（Model Element） 如类、对象、消息以及这些 ......
Understanding seconds UML in

安装CentOS7 解决错误信息:Warning: /deu/root does not exist Generating

在给一台老旧的 Dell R710安装CentOS7 时发现的一个错误 "Warning: /deu/root does not exist Generating" 看了好多的解决办法.总结来说出现此错误可以理解为 未找到安装系统盘的位置 未能找到引导 我所导致出现这个错误的原因比较奇葩 跟在网上查 ......
Generating 错误 CentOS7 Warning CentOS

开课吧前端1期.阶段2：ES6详解-4 Promise generator-认识生成器函数 generator-yield

10、Promise Promise -- 承诺 异步: 操作之间没啥关系，同时进行多个操作 同步: 同时只能做一件事 优缺点 异步：代码更复杂 同步：代码简单 //比如我要请求4个数据，真正生产还要判断，没法看了，缩进 //异步：特别麻烦 ajax('/banners',function(bann ......
generator 生成器 generator-yield 前端 函数

Seeing What You Said: Talking Face Generation Guided by a Lip Reading Expert 论文笔记

最近一直在看虚拟人像. 最关键的论文就是wav2lip. 目前项目中也是用的这个. 一个视频加一个语音, 就可以生成用视频里面的头,加语音的新视频. 现在看这篇论文Seeing What You Said: Talking Face Generation Guided by a Lip Readin ......
Generation Reading Talking 笔记 Seeing

Proj CDeepFuzz Paper Reading: Metamorphic Testing of Deep Learning Compilers

## Abstract 背景：Compiling DNN models into high-efficiency executables is not easy: the compilation procedure often involves converting high-level model ......
Metamorphic CDeepFuzz Compilers Learning Reading

《PROMPT2MODEL: Generating Deployable Models from Natural Language Instructions》论文学习

一、Introduction 传统上，从零开始构建一个自然语言处理（NLP）模型是一项重大任务。一个寻求解决新问题的NLP从业者需要定义他们的任务范围，找到或创建目标任务领域的行为数据，选择合适的模型架构，训练模型，通过评估评估其性能，然后将其部署到实际应用中。 Prompt2Model is a ......
PROMPT2MODEL Instructions Generating Deployable Language

Proj CDeepFuzz Paper Reading: A Comprehensive Study of Deep Learning Compiler Bugs

## Abstract 背景：深度学习编译器处理的深度学习模型与命令式程序有根本的不同，因为深度学习模型中的程序逻辑是隐式的。（the DL models processed by DL compilers differ fundamentally from imperative programs ......
Comprehensive CDeepFuzz Compiler Learning Reading

Proj CDeepFuzz Paper Reading: DeepMutation: Mutation Testing of Deep Learning Systems

## Abstract 本文：DeepMutation Github: https://github.com/berkuva/mutation-testing-for-DNNs Task: mutation testing framework specialized for DL systems t ......
DeepMutation CDeepFuzz Mutation Learning Reading

Proj CDeepFuzz Paper Reading: Testing Deep Neural Networks

## Abstract 本文:DeepCover Github: https://github.com/TrustAI/DeepCover Task: propose 4 novel test criteria to test DNNs Method: inspired by MC/DC cover ......
CDeepFuzz Networks Reading Testing Neural

Proj CDeepFuzz Paper Reading: TensorFlow: a system for Large-Scale machine learning

## Abstract 本文:Tensorflow Github: https://github.com/tensorflow/tensorflow Task: Detail on Tensorflow dataflow model 特点: 1. operates at large scale an ......
Large-Scale TensorFlow CDeepFuzz learning Reading

Proj CDeepFuzz Paper Reading: SparseProp: Efficient Sparse Backpropagation for Faster Training of Neural Networks

## Abstract 本文：SparseProp Github: https://github.com/IST-DASLab/sparseprop Task: a back-propagation algo for sparse training data, a fast vectorized i ......
Backpropagation SparseProp CDeepFuzz Efficient Networks

Proj CDeepFuzz Paper Reading: PyTorch: an imperative style, high-performance deep learning library

## Abstract 本文： PyTorch Task: detail the implementation and architecture of PyTorch Github: https://github.com/pytorch/pytorch 特点： 1. PyTorch同时关注可用性和速 ......
high-performance performance imperative CDeepFuzz learning

Proj CDeepFuzz Paper Reading: Software Testing with Large Language Model: Survey, Landscape, and Vision

## Abstract 本文: Task: Review on the use of LLMs in software testing Method: 1. analyzes 52 relevant studies ## 1. Intro ![](https://img2023.cnblogs.co ......
CDeepFuzz Landscape Language Software Reading

Proj CDeepFuzz Paper Reading: PELICAN: Exploiting Backdoors of Naturally Trained Deep Learning Models In Binary Code Analysis

## Abstract 背景： 1. 本文研究的不是被恶意植入的后门，而是products of defects in training 2. 攻击模式: injecting some small fixed input pattern(backdoor) to induce misclassifi ......
Exploiting CDeepFuzz Backdoors Naturally Analysis

Proj CDeepFuzz Paper Reading: Decompiling x86 Deep Neural Network Executables

## Abstract 本文: BTD github: https://github.com/monkbai/DNN-decompiler/ Task: a decompiler for DNN models to output DNN specifications including: opera ......
Decompiling Executables CDeepFuzz Network Reading

Proj CDeepFuzz Paper Reading: Balancing Effectiveness and Flakiness of Non-Deterministic Machine Learning Tests

## Abstract 背景：In fact, some of the latest findings suggest that the existence of adversarial attacks may be an inherent weakness of deep learning mod ......
Non-Deterministic Effectiveness Deterministic CDeepFuzz Balancing

Proj CDeepFuzz Paper Reading: NeuRI: Diversifying DNN Generation via Inductive Rule Inference

## Abstract 背景：The correctness of DL systems is crucial for trust in DL applications 本文: NeuRI BaseTool: FreeFuzz Github: https://github.com/ise-uiuc/ ......
Diversifying Generation CDeepFuzz Inductive Inference

Proj CDeepFuzz Paper Reading: Natural attack for pre-trained models of code

## Abstract 背景：目前大多数的adversarial attack method on pre-trained models of code忽略了perturbations should be natural to human judges(naturalness requirement ......
pre-trained CDeepFuzz Natural Reading trained

Proj CDeepFuzz Paper Reading: COMET: Coverage-guided Model Generation For Deep Learning Library Testing

## Abstract 背景：已有的方法(Muffin, Lemon, Cradle) can cover at most 34.1% layer inputs, 25.9% layer parameter values, and 15.6% layer sequences. 本文：COMET Gi ......
Coverage-guided Generation CDeepFuzz Coverage Learning

Proj CDeepFuzz Paper Reading: IvySyn: Automated Vulnerability Discovery in Deep Learning Frameworks

## Abstract 本文：IvySyn Task: discover memory error vulnerabilities in DL frameworks BugType: memory safety errors, fatal runtime errors Method: 1. 利用na ......
Vulnerability Frameworks CDeepFuzz Automated Discovery

express-generator_express-generator脚手架的安装与使用

### 安装 ``` npm install -g express-generator ``` ### 创建一个脚手架 ``` express --no-view express_generator ``` - 如上代码, 在当前目录下的expresss_generator目录创建一个应用 ### ......
express express-generator_express-generat 脚手架 generator generat

【ICML2022】Understanding The Robustness in Vision Transformers

来自NUS&NVIDIA 文章地址：[2204.12451] Understanding The Robustness in Vision Transformers (arxiv.org) 项目地址：https://github.com/NVlabs/FAN 一、Motivation CNN使用滑动 ......
Understanding Transformers Robustness Vision ICML

Proj CDeepFuzz Paper Reading: Invariance-inducing regularization using worst-case transformations suffices to boost accuracy and spatial robustness

## Abstract 本文： Task: 1. prove invariance-inducing regularizers can increase predictive accuracy for worst-case spatial transformations 2. prove that ......
Invariance-inducing transformations regularization Invariance robustness

Proj CDeepFuzz Paper Reading: Framework for Evaluating Faithfulness of Local Explanations

## Abstract 本文: Task: 1. study the faithfulness of an explanation system to the underlying prediction model on consistency and sufficiency 2. introduc ......
Faithfulness Explanations Evaluating CDeepFuzz Framework

IIncrementalGenerator 增量 Source Generator 生成代码入门 读取 csproj 项目文件的属性配置

本文告诉大家如何在使用 IIncrementalGenerator 进行增量的 Source Generator 生成代码时，读取项目里的项目文件属性，从而实现为项目定制的逻辑。或者是读取 NuGet 包里面的一些配置，从而方便实现逻辑 使用增量的源代码生成具有更高的门槛。本文属于入门博客，但非编程 ......
IIncrementalGenerator 增量 Generator 属性 代码

IIncrementalGenerator 增量 Source Generator 生成代码入门 从语法到语义 获取类型完全限定名

本文告诉大家如何在使用 IIncrementalGenerator 进行增量的 Source Generator 生成代码时，如何从语法分析过程，将获取的语法 Token 转换到语义分析上，比如获取类型完全限定名。一个使用的例子是在拿到一个 Token 表示某个类型时，本文将演示通过语义分析获取到拿 ......
语义 IIncrementalGenerator 增量 语法 Generator

dotnet 6 在 System.Text.Json 使用 source generation 源代码生成提升 JSON 序列化性能

这是一个在 dotnet 6 早就引入的功能，此功能的使用方法能简单，提升的效果也很棒。使用的时候需要将 Json 序列化工具类换成 dotnet 运行时自带的 System.Text.Json 进行序列化，再加上约 5 行的辅助代码，即可完成对接 官方文档： [如何在 System.Text.Js ......
序列 源代码 generation 性能 dotnet

Proj CDeepFuzz Paper Reading: Differential Testing of Cross Deep Learning Framework APIs: Revealing Inconsistencies and Vulnerabilities

## Abstract 背景：目前对cross-framework conversion中的inconsistencies和security bugs的研究少有 本文：TensorScope Task: test cross-frame APIs in Machine Learning Librar ......
Inconsistencies Vulnerabilities Differential CDeepFuzz Framework

Proj CDeepFuzz Paper Reading: DeepTest: automated testing of deep-neural-network-driven autonomous cars

## Abstract 本文: DeepTest Task: a systematic testing tool for DNN-driven vehicles Method: 1. generated test cases with real-world changes like rain, fo ......
deep-neural-network-driven autonomous CDeepFuzz automated DeepTest

Proj CDeepFuzz Paper Reading: DeepGauge: multi-granularity testing criteria for deep learning systems

## Abstract 本文: DeepGauge Task: provide multi-granularity testing criteria for DL systems Method: multi-granularity testing criteria for DL systems: 1 ......
multi-granularity granularity CDeepFuzz DeepGauge criteria
共270篇  :4/9页 首页上一页4下一页尾页