AWhat changed
Adapted byte-pair compression ideas to learn character-sequence merges within words, representing rare and unseen words as reusable subword sequences in neural translation.
Scientific scope
Adapted byte-pair compression ideas to learn character-sequence merges within words, representing rare and unseen words as reusable subword sequences in neural translation. The adaptation merges characters or character sequences, not necessarily raw bytes. It inherits Gage's compression algorithm and earlier subword ideas. A finite alphabet and learned representation do not guarantee correct translation of every unseen string.
Evidence
The linked original sources describe the stated contribution and its evidence limits. WRS has not independently rerun the experiments or certified a proof. The adaptation merges characters or character sequences, not necessarily raw bytes. It inherits Gage's compression algorithm and earlier subword ideas. A finite alphabet and learned representation do not guarantee correct translation of every unseen string.
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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