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Pre-trained representations reduce the need for many heavily-engineered task-specific architectures.

Drawn from what Kristina Toutanova, Kenton Lee and 2 others said

Subjectneural networks
What this subject means

neural networks The architecture almost all modern machine learning is built on, and what changes when it gets deeper.

What they actually said

  1. Kristina Toutanova One of the four authors of the 2018 paper "BERT:… We show that pre-trained representations reduce the need for many heavily-engineered task-specific architectures. BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingarxiv.org · 11 Oct 2018All 16 korrents from this piece
    Their wordsWe show that pre-trained representations reduce the need for many heavily-engineered task-specific architectures.

    Where this was said

    ↗BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingarxiv.org

    11 Oct 2018

    All 16 korrents from this piecethis one is 12th

  2. Kenton Lee One of the four authors of the 2018 paper "BERT:… We show that pre-trained representations reduce the need for many heavily-engineered task-specific architectures. BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingarxiv.org · 11 Oct 2018All 16 korrents from this piece
    Their wordsWe show that pre-trained representations reduce the need for many heavily-engineered task-specific architectures.

    Where this was said

    ↗BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingarxiv.org

    11 Oct 2018

    All 16 korrents from this piecethis one is 11th

  3. Ming-Wei Chang One of the four authors of the 2018 paper "BERT:… We show that pre-trained representations reduce the need for many heavily-engineered task-specific architectures. BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingarxiv.org · 11 Oct 2018All 16 korrents from this piece
    Their wordsWe show that pre-trained representations reduce the need for many heavily-engineered task-specific architectures.

    Where this was said

    ↗BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingarxiv.org

    11 Oct 2018

    All 16 korrents from this piecethis one is 10th

  4. Jacob Devlin One of the four authors of the 2018 paper "BERT:… We show that pre-trained representations reduce the need for many heavily-engineered task-specific architectures. BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingarxiv.org · 11 Oct 2018All 16 korrents from this piece
    Their wordsWe show that pre-trained representations reduce the need for many heavily-engineered task-specific architectures.

    Where this was said

    ↗BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingarxiv.org

    11 Oct 2018

    All 16 korrents from this piecethis one is 9th

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