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Mickel Liu

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#artificial intelligence Preprint Oct 2026

Reflections and Fragments: Securing LLMs Against Sequential Mosaic Attacks

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 attacks: multi-turn sequences whose individual fragments are innocuous in isolation yet assemble into a harmful payload. We develop a theor...

Emanuele La Malfa, Saar Cohen, G. La Malfa et al. · 0 citations
Preprint Aug 2026

SPADE: Self-Play in Adaptive Synthetic Executable Environments

SPADE (Self-Play in Adaptive Synthetic Executable Executable Environments), a self-play RL framework in which a single LLM plays two roles: an Environment Designer that writes complete, long-horizon training environments as executable code with an OpenAI Gym-style reset()/step() interface, and a Reasoning Agent that le...

Bo Liu, Simon Yu, Yiding Jiang et al. · 7 citations
#artificial intelligence Preprint Aug 2026

SPADE: Self-Play in Adaptive Synthetic Executable Environments

SPADE (Self-Play in Adaptive Synthetic Executable Executable Environments), a self-play RL framework in which a single LLM plays two roles: an Environment Designer that writes complete, long-horizon training environments as executable code with an OpenAI Gym-style reset()/step() interface, and a Reasoning Agent that le...

Bo Liu, Simon Yu, Yiding Jiang et al. · 1 citation

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