What is recorded here?
Kept a learned BPE merge table while randomly suppressing candidate merges during training segmentation, exposing the translation model to multiple segmentations before deterministic inference.
Source-linked catalogue note. A detailed explanatory guide has not yet been prepared for this entry.
Scientific scope
Does not introduce a new BPE vocabulary or establish universal robustness. Dropout acts on merge operations, not neural activations. It inherits subword regularization's motivation and uses standard BPE when the dropout probability is zero.
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People and systems
Ivan Provilkov; Dmitrii Emelianenko; Elena Voita
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.
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English catalogue narrative
BPE-dropout: stochastic merge suppression for subword training
Kept a learned BPE merge table while randomly suppressing candidate merges during training segmentation, exposing the translation model to multiple segmentations before deterministic inference.
Scientific scope
Does not introduce a new BPE vocabulary or establish universal robustness. Dropout acts on merge operations, not neural activations. It inherits subword regularization's motivation and uses standard BPE when the dropout probability is zero.
Reading status
This is a source-linked WRS catalogue note. A full explanatory guide and independent scientific reconstruction have not been completed for this entry. Read the identified original work for its complete narrative and arguments.
People and systems
Ivan Provilkov; Dmitrii Emelianenko; Elena Voita
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.