2020

Insertion-Deletion Transformer

Ruis, Laura, Stern, Mitchell, Proskurnia, Julia et al.

Understand

We propose the Insertion-Deletion Transformer, a novel transformer-based neural architecture and training method for sequence generation.

  • The model consists of two phases that are executed iteratively, 1) an insertion phase and 2) a deletion phase.
  • The insertion phase parameterizes a distribution of insertions on the current output hypothesis, while the deletion phase parameterizes a distribution of deletions over the current output hypothesis.
  • The training method is a principled and simple algorithm, where the deletion model obtains its signal directly on-policy from the insertion model output.

Built on

  • Learning Phrase Representations using RNN Encoder-Decoder for Statistical Machine Translation

    Kyunghyun Cho, Bart van Merrienboer, Caglar Gulcehre, Dzmitry Bahdanau, Fethi Bougares, Holger Schwenk, and Yoshua Bengio. 2014 · 2014

    Earlier work this paper cites.

  • Sequence to Sequence Learning with Neural Networks

    Ilya Sutskever, Oriol Vinyals, and Quoc Le. 2014 · 2014

    Earlier work this paper cites.

  • Attention Is All You Need

    Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N. Gomez, Lukasz Kaiser, and Illia Polosukhin. 2017 · 2017

    Earlier work this paper cites.

  • Deliberation networks: Sequence generation beyond one-pass decoding

    Yingce Xia, Fei Tian, Lijun Wu, Jianxin Lin, Tao Qin, Nenghai Yu, and Tie-Yan Liu. 2017 · 2017

    Earlier work this paper cites.

Similar

  • BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

    Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2018 · 2018

    Cited alongside, same era.

  • KERMIT: Generative Insertion-Based Modeling for Sequences

    William Chan, Nikita Kitaev, Kelvin Guu, Mitchell Stern, and Jakob Uszkoreit. 2019 · 2019

    Cited alongside, same era.

  • EditNTS: An Neural Programmer-Interpreter Model for Sentence Simplification through Explicit Editing

    Yue Dong, Zichao Li, Mehdi Rezagholizadeh, and Jackie Chi Kit Cheung. 2019 · 2019

    Cited alongside, same era.

  • Insertion-based Decoding with Automatically Inferred Generation Order

    Jiatao Gu, Qi Liu, and Kyunghyun Cho. 2019a

    Cited in the paper.

  • Levenshtein Transformer

    Jiatao Gu, Changhan Wang, and Jake Zhao. 2019b

    Cited in the paper.

Then

  • Optimal Completion Distillation for Sequence Learning

    Sara Sabour, William Chan, and Mohammad Norouzi. 2019 · 2019

    Later among the works it cites.

  • Insertion Transformer: Flexible Sequence Generation via Insertion Operations

    Mitchell Stern, William Chan, Jamie Kiros, and Jakob Uszkoreit. 2019 · 2019

    Later among the works it cites.

  • Non-Monotonic Sequential Text Generation

    Sean Welleck, Kiante Brantley, Hal Daume, and Kyunghyun Cho. 2019 · 2019

    Later among the works it cites.

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