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Paper · arXiv

DeepInsight II: One Trace from Benchmark to Robot

Across a Physical AI stack, evaluation maturity is inversely aligned with deployment risk: foundation models enjoy mature, standardized harnesses, while the embodied layers on which deployment actually turns remain fragmented across benchmark-specific simulators, embodiments, and interfaces. The first DeepInsight report (v1) unified evaluation across this stack behind three abstractions---task, resource, and result---but its quantitative evidence centered on the foundation-model layer; navigation and manipulation (System 1) and whole-body control (System 0) remained simulation case studies, and physical execution was outside its empirical scope. DeepInsight II keeps that substrate fixed a...

AuthorsSiyi Li, Yuchen Kang, Wuliang Wang et al.
Primary categorycs.AI
Published17 August 2026
Last updated at source17 August 2026
cs.AI
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