bymavis's repositories

Adv_Weight_NeurIPS2021

The official code (PyTorch version) for paper 'Clustering Effect of Adversarial Robust Models'. (accepted by NeurIPS 2021, Spotlight)

Language:PythonStargazers:7Issues:1Issues:0

3-Phish-Page-Detection

A machine learning based phishing detection prototype

Language:PythonStargazers:0Issues:0Issues:0
Stargazers:0Issues:0Issues:0
Language:PythonStargazers:0Issues:0Issues:0

bymavis.github.io

My homepage's source code

Language:CSSLicense:CC0-1.0Stargazers:0Issues:0Issues:0

CodeT5

Code for CodeT5: a new code-aware pre-trained encoder-decoder model.

Language:PythonLicense:BSD-3-ClauseStargazers:0Issues:0Issues:0

CodeXGLUE

CodeXGLUE

Language:C#License:MITStargazers:0Issues:0Issues:0

ColossalAI

Making big AI models cheaper, easier, and more scalable

Language:PythonLicense:Apache-2.0Stargazers:0Issues:0Issues:0
Language:PythonLicense:MITStargazers:0Issues:0Issues:0

devign

Effective Vulnerability Identification by Learning Comprehensive Program Semantics via Graph Neural Networks

Language:PythonLicense:MITStargazers:0Issues:0Issues:0

evals

Evals is a framework for evaluating OpenAI models and an open-source registry of benchmarks.

Language:PythonLicense:MITStargazers:0Issues:0Issues:0

neural-anisotropy-directions

Source code for "Neural Anisotropy Directions"

License:Apache-2.0Stargazers:0Issues:0Issues:0

ODGen

ODGen is a tool to detect multiple types of vulnerabilities in Node.js packages.

Stargazers:0Issues:0Issues:0

oldversion_joern

deepwukkong_preprocess

Language:JavaStargazers:0Issues:0Issues:0

PhishingBaseline

Implementations of 3 phishing detection and identification baselines

Stargazers:0Issues:0Issues:0

PhishIntention

PhishIntention: Phishing detection through webpage intention

License:MITStargazers:0Issues:0Issues:0

Phishpedia

Official Implementation of "Phishpedia: A Hybrid Deep Learning Based Approach to Visually Identify Phishing Webpages" USENIX'21

Language:PythonLicense:MITStargazers:0Issues:0Issues:0
License:MITStargazers:0Issues:0Issues:0

stanford_alpaca

Code and documentation to train Stanford's Alpaca models, and generate the data.

License:Apache-2.0Stargazers:0Issues:0Issues:0

stealing-part-of-an-LM

An unofficial implementation of "Stealing Part of a Production Language Model"

License:MITStargazers:0Issues:0Issues:0
Language:HTMLStargazers:0Issues:0Issues:0

Untargeted_Backdoor_Watermark

This is the official implementation of our paper 'Untargeted Backdoor Watermark: Towards Harmless and Stealthy Dataset Copyright Protection', accepted in NeurIPS 2022.

Language:PythonLicense:Apache-2.0Stargazers:0Issues:0Issues:0