Our paper Less is More: Boosting Coverage of Web Crawling through Adversarial Multi-Armed Bandit has been accepted at DSN 2025! In this work, we propose a new state-agnostic Reinforcement Learning-based crawler that applies Adversarial Multi-Armed Bandit in a smart way to improve the exploration of web applications, surpassing the limitations of previous crawlers based on Reinforcement Learning. Available soon!