Beyond Noise: Mitigating the Impact of Fine-grained Semantic Divergences
on Neural Machine Translation

Beyond Noise: Mitigating the Impact of Fine-grained Semantic Divergences on Neural Machine Translation

31 May 2021

Eleftheria Briakou

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Papers citing "Beyond Noise: Mitigating the Impact of Fine-grained Semantic Divergences on Neural Machine Translation"

8 / 8 papers shown

Title
How to Learn in a Noisy World? Self-Correcting the Real-World Data Noise in Machine Translation Yan Meng Di Wu Christof Monz 101 1 0 02 Jul 2024
Cultural Adaptation of Recipes Yong Cao Yova Kementchedjhieva Ruixiang Cui Antonia Karamolegkou Li Zhou Megan Dare Lucia Donatelli Daniel Hershcovich 95 6 0 26 Oct 2023
Understanding and Detecting Hallucinations in Neural Machine Translation via Model Introspection Weijia Xu Sweta Agrawal Eleftheria Briakou Marianna J. Martindale Marine Carpuat HILM 78 49 0 18 Jan 2023
Measuring Fine-Grained Semantic Equivalence with Abstract Meaning Representation Shira Wein Zhuxin Wang Nathan Schneider 63 3 0 06 Oct 2022
Challenges and Strategies in Cross-Cultural NLP Daniel Hershcovich Stella Frank Heather Lent Miryam de Lhoneux Mostafa Abdou ... Ruixiang Cui Constanza Fierro Katerina Margatina Phillip Rust Anders Søgaard 130 182 0 18 Mar 2022
Can Synthetic Translations Improve Bitext Quality? Eleftheria Briakou Marine Carpuat 60 5 0 15 Mar 2022
Survey of Hallucination in Natural Language Generation Ziwei Ji Nayeon Lee Rita Frieske Tiezheng Yu D. Su ... Delong Chen Wenliang Dai Ho Shu Chan Andrea Madotto Pascale Fung HILM LRM 337 2,492 0 08 Feb 2022
BitextEdit: Automatic Bitext Editing for Improved Low-Resource Machine Translation Eleftheria Briakou Sida Wang Luke Zettlemoyer Marjan Ghazvininejad 43 5 0 12 Nov 2021