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Convolutional sequence-to-sequence learning with multi-step attention

Used residual gated convolutions for source and target sequence representations, with separate attention at decoder layers and parallel computation across training positions.

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Used residual gated convolutions for source and target sequence representations, with separate attention at decoder layers and parallel computation across training positions.

Source-linked catalogue note. A detailed explanatory guide has not yet been prepared for this entry.

Scientific scope

Training parallelism does not remove autoregressive dependencies during generation. GLUs, residual learning, convolutions and attention are inherited components. Benchmarked speed/quality improvements are not a universal advantage over recurrent or Transformer models.

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People and systems

Jonas Gehring; Michael Auli; David Grangier; Denis Yarats; Yann N. Dauphin

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

Convolutional sequence-to-sequence learning with multi-step attention

Used residual gated convolutions for source and target sequence representations, with separate attention at decoder layers and parallel computation across training positions.

Scientific scope

Training parallelism does not remove autoregressive dependencies during generation. GLUs, residual learning, convolutions and attention are inherited components. Benchmarked speed/quality improvements are not a universal advantage over recurrent or Transformer models.

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

Jonas Gehring; Michael Auli; David Grangier; Denis Yarats; Yann N. Dauphin

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.

Original sources