What is recorded here?
Used permutations of autoregressive factorization and a two-stream attention design to learn bidirectional language representations.
Source-linked catalogue note. A detailed explanatory guide has not yet been prepared for this entry.
Scientific scope
Factorization order is permuted, not necessarily the input token positions. Transformer-XL recurrence is inherited; benchmark gains are not universal dominance.
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People and systems
Zhilin Yang; Zihang Dai; Yiming Yang; Jaime Carbonell; Ruslan Salakhutdinov; Quoc V. Le
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
Yang and colleagues: XLNet permutation language-model pre-training
Used permutations of autoregressive factorization and a two-stream attention design to learn bidirectional language representations.
Scientific scope
Factorization order is permuted, not necessarily the input token positions. Transformer-XL recurrence is inherited; benchmark gains are not universal dominance.
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
Zhilin Yang; Zihang Dai; Yiming Yang; Jaime Carbonell; Ruslan Salakhutdinov; Quoc V. Le
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.