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This work presents ZGCM-1, a fully open 7B dense foundation model trained from scratch with extreme data, system, and algorithmic efficiency, and establishes an AI-native R&D workflow where agent swarms autonomously manage cluster operations, data curation, and rapid diagnostic evaluation.
TAMP-Nav aligns embodied navigation with VLMs' 2D capabilities, achieving a 66.2% success rate while drastically improving efficiency.