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The proposed convention gap is a metric of implicit communication that suggests that convention compatibility, rather than AI-AI performance, may predict an AI's effectiveness with human partners.
SkillComposer achieves a remarkable +23.1% increase in task success rates for LLM agents by rethinking how skills are composed and executed together.
Text, combined with learned image embeddings, can compress maps by 2x while preserving localization accuracy, offering a practical solution to the growing memory demands of robotic mapping.
