HAM³ achieves up to 78.3% attack success rate on the GQA benchmark by hierarchically attacking perception, communication, and reasoning layers in multi-modal multi-agent systems.
Caml: Collaborative auxiliary modality learning for multi-agent systems
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CRONA is a MARL framework that uses modality-specialized agents with auxiliary beliefs and a centralized multi-modal critic to achieve better performance and efficiency than single-agent baselines on visual-acoustic navigation tasks.
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Hierarchical Attacks for Multi-Modal Multi-Agent Reasoning
HAM³ achieves up to 78.3% attack success rate on the GQA benchmark by hierarchically attacking perception, communication, and reasoning layers in multi-modal multi-agent systems.
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Cross-Modal Navigation with Multi-Agent Reinforcement Learning
CRONA is a MARL framework that uses modality-specialized agents with auxiliary beliefs and a centralized multi-modal critic to achieve better performance and efficiency than single-agent baselines on visual-acoustic navigation tasks.