[NeurIPS 2024] OSWorld: Benchmarking Multimodal Agents for Open-Ended Tasks in Real Computer Environments

A tool that validates academic paper references

PyMuPDF is a high performance Python library for data extraction, analysis, conversion & manipulation of PDF (and other) documents.

A web app for ranking computer science departments according to their research output in selective venues, and for finding active faculty across a wide range of areas.

A helper package to get information of scholarly articles from DBLP using its public API

The official Python SDK for Model Context Protocol servers and clients

A python interface for training Reinforcement Learning bots to battle on pokemon showdown

🚀 The fast, Pythonic way to build MCP servers and clients

DNS-Blocklists: For a better internet - keep the internet clean!

Repository for the evaluation of the transferabiilty of adversarial examples.

A collection of awesome resources related AI security

A collection of sample agents built with Agent Development Kit (ADK)

TabularBench: Adversarial robustness benchmark for tabular data

NFStream: a Flexible Network Data Analysis Framework.

PCLA: A framework for testing autonomous agents in the CARLA simulator

12 Lessons to Get Started Building AI Agents

MetaDrive: Lightweight driving simulator for everyone

TaskTracker is an approach to detecting task drift in Large Language Models (LLMs) by analysing their internal activations. It provides a simple linear probe-based method and a more sophisticated m…

Accompanying code and SEP dataset for the "Can LLMs Separate Instructions From Data? And What Do We Even Mean By That?" paper.

Experiments for paper ModSec-AdvLearn: Countering Adversarial SQL Injections with Robust Machine Learning

Open-source scientific and technical publishing system built on Pandoc.

optimizer & lr scheduler & loss function collections in PyTorch

Run safety benchmarks against AI models and view detailed reports showing how well they performed.

A Visual Studio Code extension with support for the Ruff linter.

PyTorch native quantization and sparsity for training and inference

The correct way to resize images or tensors. For Numpy or Pytorch (differentiable).

Fast and accurate AI powered file content types detection