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        <title>Exploration of the CycleGN Framework for Low-Resource Languages</title>
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        <namePart type="given">Sören</namePart>
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    <name type="personal">
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            <title>Proceedings of the Ninth Conference on Machine Translation</title>
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            <namePart type="given">Christof</namePart>
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    <abstract>CycleGN is a Neural Machine Translation framework relying on the Transformer architecture. The foundational concept of our research posits that in an ideal scenario, retro-translations of generated translations should revert to the original source sentences. Consequently, a pair of models can be trained using a Cycle Consistency Loss only, with one model translating in one direction and the second model in the opposite direction.</abstract>
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%0 Conference Proceedings
%T Exploration of the CycleGN Framework for Low-Resource Languages
%A Dreano, Sören
%A Molloy, Derek
%A Murphy, Noel
%Y Haddow, Barry
%Y Kocmi, Tom
%Y Koehn, Philipp
%Y Monz, Christof
%S Proceedings of the Ninth Conference on Machine Translation
%D 2024
%8 November
%I Association for Computational Linguistics
%C Miami, Florida, USA
%F dreano-etal-2024-exploration
%X CycleGN is a Neural Machine Translation framework relying on the Transformer architecture. The foundational concept of our research posits that in an ideal scenario, retro-translations of generated translations should revert to the original source sentences. Consequently, a pair of models can be trained using a Cycle Consistency Loss only, with one model translating in one direction and the second model in the opposite direction.
%U https://aclanthology.org/2024.wmt-1.66
%P 756-761

Markdown (Informal)

[Exploration of the CycleGN Framework for Low-Resource Languages](https://aclanthology.org/2024.wmt-1.66) (Dreano et al., WMT 2024)

• Exploration of the CycleGN Framework for Low-Resource Languages (Dreano et al., WMT 2024)

ACL

• Sören Dreano, Derek Molloy, and Noel Murphy. 2024. Exploration of the CycleGN Framework for Low-Resource Languages. In Proceedings of the Ninth Conference on Machine Translation, pages 756–761, Miami, Florida, USA. Association for Computational Linguistics.