arXiv AI By Xue Qin, Simin Luan, Cong Yang, Zhijun Li

Bounded-Fidelity Sim-as-Demo-Stage: Mocap Handoff for Governance Benchmarks

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The paper introduces a bounded‑fidelity sim‑as‑demo‑stage design pattern that suppresses contact physics during object handoffs in simulators, using MuJoCo’s mocap‑body primitive and a lightweight Python adapter. This approach ensures audit‑chain stability, producing identical event‑log hashes across 1,000 replays per posture, whereas a contact‑force baseline yields significant divergence. The authors demonstrate that the pattern maintains reproducibility across various timesteps and sequential handoffs with minimal overhead, and they identify contexts where it should not be applied.

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arXiv AI
Aug 18

DeepInsight II: One Trace from Benchmark to Robot

arXiv:2608. 16556v1 Announce Type: new Abstract: 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.

By Siyi Li, Yuchen Kang, Wuliang Wang, Zhengjie Zhang, Jiangpin Liu, Jianhao Yao, Jie Chen