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        <title>Exploring Looping Effects in RNN-based Architectures</title>
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        <namePart type="given">Andrei</namePart>
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    <name type="personal">
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    <abstract>The paper investigates repetitive loops, a common problem in contemporary text generation (such as machine translation, language modelling, morphological inflection) systems. More specifically, we conduct a study on neural models with recurrent units by explicitly altering their decoder internal state. We use a task of morphological reinflection task as a proxy to study the effects of the changes. Our results show that the probability of the occurrence of repetitive loops is significantly reduced by introduction of an extra neural decoder output. The output should be specifically trained to produce gradually increasing value upon generation of each character of a given sequence. We also explored variations of the technique and found that feeding the extra output back to the decoder amplifies the positive effects.</abstract>
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%0 Conference Proceedings
%T Exploring Looping Effects in RNN-based Architectures
%A Shcherbakov, Andrei
%A Muradoglu, Saliha
%A Vylomova, Ekaterina
%S Proceedings of the The 18th Annual Workshop of the Australasian Language Technology Association
%D 2020
%8 dec
%I Australasian Language Technology Association
%C Virtual Workshop
%F shcherbakov-etal-2020-exploring
%X The paper investigates repetitive loops, a common problem in contemporary text generation (such as machine translation, language modelling, morphological inflection) systems. More specifically, we conduct a study on neural models with recurrent units by explicitly altering their decoder internal state. We use a task of morphological reinflection task as a proxy to study the effects of the changes. Our results show that the probability of the occurrence of repetitive loops is significantly reduced by introduction of an extra neural decoder output. The output should be specifically trained to produce gradually increasing value upon generation of each character of a given sequence. We also explored variations of the technique and found that feeding the extra output back to the decoder amplifies the positive effects.
%U https://aclanthology.org/2020.alta-1.15
%P 115-120

Markdown (Informal)

[Exploring Looping Effects in RNN-based Architectures](https://aclanthology.org/2020.alta-1.15) (Shcherbakov et al., ALTA 2020)

• Exploring Looping Effects in RNN-based Architectures (Shcherbakov et al., ALTA 2020)

ACL

• Andrei Shcherbakov, Saliha Muradoglu, and Ekaterina Vylomova. 2020. Exploring Looping Effects in RNN-based Architectures. In Proceedings of the The 18th Annual Workshop of the Australasian Language Technology Association, pages 115–120, Virtual Workshop. Australasian Language Technology Association.