A generative-adversarial-exam-based quality-of-memory metric drives memory-centric power allocation that prioritizes high-memory robots and improves multi-agent embodied question answering.
Towards top-down reasoning: An explainable multi-agent approach for visual question answering
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Memory Centric Power Allocation for Multi-Agent Embodied Question Answering
A generative-adversarial-exam-based quality-of-memory metric drives memory-centric power allocation that prioritizes high-memory robots and improves multi-agent embodied question answering.