--- title: "Machine translation — paper cards, page 2" description: "Machine translation: 310 paper cards of the Elamur Research library · page 2 of 13." canonical: "https://research.elamur.ai/free/en/shelves/mtrans/page/2/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/shelves/mtrans/page/2/) [home](https://md.research.elamur.ai/free/en/) / [shelves](https://md.research.elamur.ai/free/en/shelves/) / [Machine translation](https://md.research.elamur.ai/free/en/shelves/mtrans/) / page 2 # Machine translation 310 cards · page 2 of 13 · newest first · [Linguistics](https://md.research.elamur.ai/free/en/shelves/linguistics/) · [all shelves](https://md.research.elamur.ai/free/en/shelves/) Interlingua and transfer, tree-to-tree, rule-based MT, generation, style and Bible translation, evaluation. [← prev](https://md.research.elamur.ai/free/en/shelves/mtrans/) [1](https://md.research.elamur.ai/free/en/shelves/mtrans/) **2** [3](https://md.research.elamur.ai/free/en/shelves/mtrans/page/3/) … [13](https://md.research.elamur.ai/free/en/shelves/mtrans/page/13/) [next →](https://md.research.elamur.ai/free/en/shelves/mtrans/page/3/) - [ParaAMR: A Large-Scale Syntactically Diverse Paraphrase Dataset by AMR Back-Translation](https://md.research.elamur.ai/free/en/papers/huang-2023-paraamr-large-scale-syntactically-diverse/) — Kuan-Hao Huang, Varun Iyer, I-Hung Hsu, et al. · 2023 - [The eBible Corpus: Data and Model Benchmarks for Bible Translation for Low-Resource Languages](https://md.research.elamur.ai/free/en/papers/akerman-2023-ebible-corpus-data-model-benchmarks/) — Vesa Akerman, David Baines, Damien Daspit, et al. · 2023 - [The Mechanical Bard: An Interpretable Machine Learning Approach to Shakespearean Sonnet Generation](https://md.research.elamur.ai/free/en/papers/agnew-2023-mechanical-bard-interpretable-machine-learning/) — Edwin Agnew, Michelle Qiu, Lily Zhu, et al. · 2023 - [UMR Annotation of Multiword Expressions](https://md.research.elamur.ai/free/en/papers/bonn-2023-umr-annotation-multiword-expressions/) — Julia Bonn, Andrew Cowell, Jan Hajič, et al. · 2023 - [ACES: Translation Accuracy Challenge Sets for Evaluating Machine Translation Metrics](https://md.research.elamur.ai/free/en/papers/amrhein-2022-aces-translation-accuracy-challenge-sets/) — Chantal Amrhein, Nikita Moghe, Liane Guillou · 2022 - [DocAMR: Multi-Sentence AMR Representation and Evaluation](https://md.research.elamur.ai/free/en/papers/naseem-2022-docamr-multi-sentence-amr-representation/) — Tahira Naseem, Austin Blodgett, Sadhana Kumaravel, et al. · 2022 - [Linguistically Motivated Evaluation of the 2022 State-of-the-art Machine Translation Systems for Three Language Directions](https://md.research.elamur.ai/free/en/papers/macketanz-2022-linguistically-motivated-evaluation-2022-state/) — Vivien Macketanz, Shushen Manakhimova, Eleftherios Avramidis, et al. · 2022 - [Low-Resource Authorship Style Transfer: Can Non-Famous Authors Be Imitated?](https://md.research.elamur.ai/free/en/papers/patel-2022-low-resource-authorship-style-transfer/) — Ajay Patel, Nicholas Andrews, Chris Callison-Burch · 2022 - [Results of WMT22 Metrics Shared Task: Stop Using BLEU – Neural Metrics Are Better and More Robust](https://md.research.elamur.ai/free/en/papers/freitag-2022-results-wmt22-metrics-shared-task/) — Markus Freitag, Ricardo Rei, Nitika Mathur, et al. · 2022 - [T-STAR: Truthful Style Transfer using AMR Graph as Intermediate Representation](https://md.research.elamur.ai/free/en/papers/jangra-2022-t-star-truthful-style-transfer/) — Anubhav Jangra, Preksha Nema, Aravindan Raghuveer · 2022 - [Unsupervised Syntactically Controlled Paraphrase Generation with Abstract Meaning Representations](https://md.research.elamur.ai/free/en/papers/huang-2022-unsupervised-syntactically-controlled-paraphrase-generation/) — Kuan-Hao Huang, Varun Iyer, Anoop Kumar, et al. · 2022 - [Acquiring a Formality-Informed Lexical Resource for Style Analysis](https://md.research.elamur.ai/free/en/papers/eder-2021-acquiring-formality-informed-lexical-resource/) — Elisabeth Eder, Ulrike Krieg-Holz, Udo Hahn · 2021 - [An Error Analysis Framework for Shallow Surface Realization](https://md.research.elamur.ai/free/en/papers/shimorina-2021-error-analysis-framework-shallow-surface/) — Anastasia Shimorina, Yannick Parmentier, Claire Gardent · 2021 - [Evaluating Text Generation from Discourse Representation Structures](https://md.research.elamur.ai/free/en/papers/wang-2021-evaluating-text-generation-discourse-representation/) — Chunliu Wang, Rik van Noord, Arianna Bisazza, et al. · 2021 - [Evaluating the Evaluation Metrics for Style Transfer: A Case Study in Multilingual Formality Transfer](https://md.research.elamur.ai/free/en/papers/briakou-2021-evaluating-evaluation-metrics-style-transfer/) — Eleftheria Briakou, Sweta Agrawal, Joel Tetreault, et al. · 2021 - [Expanding the JHU Bible Corpus for Machine Translation of the Indigenous Languages of North America](https://md.research.elamur.ai/free/en/papers/nicolai-2021-expanding-jhu-bible-corpus-machine/) — Garrett Nicolai, Edith Coates, Ming Zhang, et al. · 2021 - [Experts, Errors, and Context: A Large-Scale Study of Human Evaluation for Machine Translation](https://md.research.elamur.ai/free/en/papers/freitag-2021-experts-errors-context-large-scale/) — Markus Freitag, George Foster, David Grangier, et al. · 2021 - [Grammar-Based Concept Alignment for Domain-Specific Machine Translation](https://md.research.elamur.ai/free/en/papers/masciolini-2021-grammar-based-concept-alignment-domain/) — Arianna Masciolini, Aarne Ranta · 2021 - [Text Generation from Discourse Representation Structures](https://md.research.elamur.ai/free/en/papers/liu-2021-text-generation-discourse-representation-structures/) — Jiangming Liu, Shay B. Cohen, Mirella Lapata · 2021 - [Towards a Decomposable Metric for Explainable Evaluation of Text Generation from AMR](https://md.research.elamur.ai/free/en/papers/opitz-2021-decomposable-metric-explainable-evaluation-text/) — Juri Opitz, Anette Frank · 2021 - [Weisfeiler-Leman in the Bamboo: Novel AMR Graph Metrics and a Benchmark for AMR Graph Similarity](https://md.research.elamur.ai/free/en/papers/opitz-2021-weisfeiler-leman-bamboo-novel-amr/) — Juri Opitz, Angel Daza, Anette Frank · 2021 - [A Survey of Qualitative Error Analysis for Neural Machine Translation Systems](https://md.research.elamur.ai/free/en/papers/diaz-2020-survey-qualitative-error-analysis-neural/) — Denise Díaz, James Cross, Vishrav Chaudhary, et al. · 2020 - [Abstract Syntax as Interlingua: Scaling Up the Grammatical Framework from Controlled Languages to Robust Pipelines](https://md.research.elamur.ai/free/en/papers/ranta-2020-abstract-syntax-as-interlingua-scaling/) — Aarne Ranta, Krasimir Angelov, Normunds Gruzitis, et al. · 2020 - [COMET: A Neural Framework for MT Evaluation](https://md.research.elamur.ai/free/en/papers/rei-2020-comet-neural-framework-mt-evaluation/) — Ricardo Rei, Craig Stewart, Ana C Farinha, et al. · 2020 - [Comparison by Conversion: Reverse-Engineering UCCA from Syntax and Lexical Semantics](https://md.research.elamur.ai/free/en/papers/hershcovich-2020-comparison-conversion-reverse-engineering-ucca/) — Daniel Hershcovich, Nathan Schneider, Dotan Dvir, et al. · 2020 [← prev](https://md.research.elamur.ai/free/en/shelves/mtrans/) [1](https://md.research.elamur.ai/free/en/shelves/mtrans/) **2** [3](https://md.research.elamur.ai/free/en/shelves/mtrans/page/3/) … [13](https://md.research.elamur.ai/free/en/shelves/mtrans/page/13/) [next →](https://md.research.elamur.ai/free/en/shelves/mtrans/page/3/)