🚀 FastAT Benchmark

📋 Overview

The FastAT Benchmark provides a rigorous and fair evaluation framework for fast adversarial training methods. Unlike public leaderboards that allow diverse combinations of model architectures, data sources, and computational budgets, our benchmark establishes conditions where all methods compete on equal footing.

This platform implements over a dozen representative FastAT methods with a unified codebase, ensuring fair and reproducible comparison across different algorithmic innovations. The benchmark systematically removes advantages from massive computational resources and unlimited external data, providing the research community with a transparent baseline for evaluating fast adversarial training techniques.