8 citations · 13 across the 8 of their papers we have counts for
3 papers · 1 filter
Reflections and Fragments: Securing LLMs Against Sequential Mosaic Attacks
Emanuele La Malfa, Saar Cohen, Gabriele La Malfa +4
Self-play red-teaming improves language-model safety by pitting attacker and defender roles against each other in a zero-sum game. However, real adversaries increasingly use mosaic…
Explore, Map, Remember, Decide: Are Embodied VLMs Ready for Safety-Critical Scenarios?
Gabriele La Malfa, Nitay Alon, Emanuele La Malfa +2
Theory of Space framework (ToS) assesses the spatial understanding of curiosity-driven Vision-Language Models (VLMs) under partial observability. As AI techniques are increasingly…
The Attacker in the Mirror: Breaking Self-Consistency in Safety via Anchored Bipolicy Self-Play
Gabriele La Malfa, Emanuele La Malfa, Saar Cohen +4
Self-play red team is an established approach to improving AI safety in which different instances of the same model play attacker and defender roles in a zero-sum game, i.e., where…