AWhat changed
Uses binarized path gates and pairwise architecture updates to reduce supernetwork memory, with latency-model gradients or REINFORCE for hardware-aware search directly on target tasks.
Scientific scope
Uses binarized path gates and pairwise architecture updates to reduce supernetwork memory, with latency-model gradients or REINFORCE for hardware-aware search directly on target tasks. Architecture gradients are approximate and latency prediction sums per-block estimates. Direct target search is not exhaustive/global optimization, nor a guarantee that searched models are fastest on unseen devices.
Evidence
The linked original sources describe the stated contribution and its evidence limits. WRS has not independently rerun the experiments or certified a proof. Architecture gradients are approximate and latency prediction sums per-block estimates. Direct target search is not exhaustive/global optimization, nor a guarantee that searched models are fastest on unseen devices.
Contributors
- Source-listed authors and technical contributors · SCIENCE: Source-listed authors or explicitly credited technical contributors for the cited versions. Family entries retain source-specific attribution; a combined list is not one original-paper byline or equal individual work. Names alone do not establish resolved identities.
Provisional WRS assessment, edition 2026-10-16.1. Independent expert calibration is pending. This grade does not certify correctness or assign ownership.
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