RoboLineage introduces an agent-native data lifecycle governance system that represents robot policy iteration steps as typed lineage artifacts to improve speed and auditability in real-robot workflows.
In: 2019 IEEE/ACM Workflows in Support of Large-Scale Science (WORKS)
2 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
years
2026 2verdicts
UNVERDICTED 2representative citing papers
H100 shows slightly higher efficiency for compute-bound workloads while H200 excels for memory-bound ones across power cap levels.
citing papers explorer
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RoboLineage: Agent-Native Data Lifecycle Governance Across Robot Policy Iterations
RoboLineage introduces an agent-native data lifecycle governance system that represents robot policy iteration steps as typed lineage artifacts to improve speed and auditability in real-robot workflows.
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Architectural Trade-offs in the Energy-Efficient Era: A Comparative Study of power-capping NVIDIA H100 and H200
H100 shows slightly higher efficiency for compute-bound workloads while H200 excels for memory-bound ones across power cap levels.