10 citations · 12 across the 4 of their papers we have counts for
4 papers
Tournament Informed Adversarial Quality Diversity
Timothée Anne, Noah Syrkis, Meriem Elhosni +5
Quality diversity (QD) is a branch of evolutionary computation that seeks high-quality and behaviorally diverse solutions to a problem. While adversarial problems are common, class…
Adversarial Coevolutionary Illumination with Generational Adversarial MAP-Elites
Timothée Anne, Noah Syrkis, Meriem Elhosni +4
Quality-Diversity (QD) algorithms seek to discover diverse, high-performing solutions across a behavior space, in contrast to conventional optimization methods that target a single…
Harnessing Language for Coordination: A Framework and Benchmark for LLM-Driven Multi-Agent Control
Timothée Anne, Noah Syrkis, Meriem Elhosni +4
Large Language Models (LLMs) have demonstrated remarkable performance across various tasks. Their potential to facilitate human coordination with many agents is a promising but lar…
Locality-Sensitive Hashing Does Not Guarantee Privacy! Attacks on Google's FLoC and the MinHash Hierarchy System
Florian Turati, Carlos Cotrini, Karel Kubicek +1
Recently proposed systems aim at achieving privacy using locality-sensitive hashing. We show how these approaches fail by presenting attacks against two such systems: Google's FLoC…