AWhat changed
Provided model/task/criterion interfaces, distributed and mixed-precision training, incremental decoding caches and reference sequence-model implementations in a reusable PyTorch toolkit.
Scientific scope
Provided model/task/criterion interfaces, distributed and mixed-precision training, incremental decoding caches and reference sequence-model implementations in a reusable PyTorch toolkit. This is a software/systems contribution, not invention of every implemented architecture, decoding rule or mixed-precision technique. The2019report extends the tool earlier released with convolutional translation; current software features are not backdated.
Evidence
The linked original sources describe the stated contribution and its evidence limits. WRS has not independently rerun the experiments or certified a proof. This is a software/systems contribution, not invention of every implemented architecture, decoding rule or mixed-precision technique. The2019report extends the tool earlier released with convolutional translation; current software features are not backdated.
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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