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# Who cites «chrF: character n-gram F-score for automatic MT evaluation» · page 7

1093 papers of our library cite it, newest first: found in their bibliographies, which we read ourselves. [← the card](https://md.mova.elamur.ai/free/en/docs/papers/popovic-2015-chrf-character-n-gram-f/)

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1. [Separating Grains from the Chaff: Using Data Filtering to Improve Multilingual Translation for Low-Resourced African Languages](https://aclanthology.org/2022.wmt-1.98/) *— 2022 · Proceedings of the Seventh Conference on Machine Translation (WMT)*
2. [Specializing Multi-domain NMT via Penalizing Low Mutual Information](https://aclanthology.org/2022.emnlp-main.680/) *— 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing*
3. [SubER - A Metric for Automatic Evaluation of Subtitle Quality](https://aclanthology.org/2022.iwslt-1.1/) *— 2022 · Proceedings of the 19th International Conference on Spoken Language Translation (IWSLT 2022)*
4. [Syntax Controlled Knowledge Graph-to-Text Generation with Order and Semantic Consistency](https://aclanthology.org/2022.findings-naacl.95/) *— 2022 · Findings of the Association for Computational Linguistics: NAACL 2022*
5. [TANDO: A Corpus for Document-level Machine Translation](https://aclanthology.org/2022.lrec-1.324/) *— 2022 · Proceedings of the Thirteenth Language Resources and Evaluation Conference*
6. [Text-to-Table: A New Way of Information Extraction](https://aclanthology.org/2022.acl-long.180/) *— 2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
7. [The HW-TSC's Speech to Speech Translation System for IWSLT 2022 Evaluation](https://aclanthology.org/2022.iwslt-1.26/) *— 2022 · Proceedings of the 19th International Conference on Spoken Language Translation (IWSLT 2022)*
8. [Translation Memories as Baselines for Low-Resource Machine Translation](https://aclanthology.org/2022.lrec-1.728/) *— 2022 · Proceedings of the Thirteenth Language Resources and Evaluation Conference*
9. [UniTE: Unified Translation Evaluation](https://aclanthology.org/2022.acl-long.558/) *— 2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
10. [Varifocal Question Generation for Fact-checking](https://aclanthology.org/2022.emnlp-main.163/) *— 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing*
11. [What Do Compressed Multilingual Machine Translation Models Forget?](https://aclanthology.org/2022.findings-emnlp.317/) *— 2022 · Findings of the Association for Computational Linguistics: EMNLP 2022*
12. [What Makes Data-to-Text Generation Hard for Pretrained Language Models?](https://aclanthology.org/2022.gem-1.50/) *— 2022 · Proceedings of the Second Workshop on Natural Language Generation, Evaluation, and Metrics (GEM)*
13. [When does Parameter-Efficient Transfer Learning Work for Machine Translation?](https://aclanthology.org/2022.emnlp-main.540/) *— 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing*
14. [Why don't people use character-level machine translation?](https://aclanthology.org/2022.findings-acl.194/) *— 2022 · Findings of the Association for Computational Linguistics: ACL 2022*
15. [gaHealth: An English–Irish Bilingual Corpus of Health Data](https://aclanthology.org/2022.lrec-1.727/) *— 2022 · Proceedings of the Thirteenth Language Resources and Evaluation Conference*
16. [m$^4$ Adapter: Multilingual Multi-Domain Adaptation for Machine Translation with a Meta-Adapter](https://aclanthology.org/2022.findings-emnlp.315/) *— 2022 · Findings of the Association for Computational Linguistics: EMNLP 2022*
17. [semiPQA: A Study on Product Question Answering over Semi-structured Data](https://aclanthology.org/2022.ecnlp-1.14/) *— 2022 · Proceedings of the Fifth Workshop on e-Commerce and NLP (ECNLP 5)*
18. [A Large-Scale Study of Machine Translation in Turkic Languages](https://aclanthology.org/2021.emnlp-main.475/) *— 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing*
19. [A Tutorial on Evaluation Metrics used in Natural Language Generation](https://aclanthology.org/2021.naacl-tutorials.4/) *— 2021 · Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies: Tutorials*
20. [AfroMT: Pretraining Strategies and Reproducible Benchmarks for Translation of 8 African Languages](https://aclanthology.org/2021.emnlp-main.99/) *— 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing*
21. [Are References Really Needed? Unbabel-IST 2021 Submission for the Metrics Shared Task](https://aclanthology.org/2021.wmt-1.111/) *— 2021 · Proceedings of the Sixth Conference on Machine Translation*
22. [Assessing Evaluation Metrics for Speech-to-Speech Translation](https://arxiv.org/abs/2110.13877) *— 2021 · arXiv:2110.13877*
23. [Automatic Text Evaluation through the Lens of Wasserstein Barycenters](https://aclanthology.org/2021.emnlp-main.817/) *— 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing*
24. [BARTScore: Evaluating Generated Text as Text Generation](https://arxiv.org/abs/2106.11520) *— 2021 · arXiv:2106.11520*
25. [Compression, Transduction, and Creation: A Unified Framework for Evaluating Natural Language Generation](https://aclanthology.org/2021.emnlp-main.599/) *— 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing*
26. [Detecting Post-Edited References and Their Effect on Human Evaluation](https://aclanthology.org/2021.humeval-1.13/) *— 2021 · Proceedings of the Workshop on Human Evaluation of NLP Systems (HumEval)*
27. [Difficulty-Aware Machine Translation Evaluation](https://aclanthology.org/2021.acl-short.5/) *— 2021 · Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 2: Short Papers)*
28. [Efficient Inference for Multilingual Neural Machine Translation](https://aclanthology.org/2021.emnlp-main.674/) *— 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing*
29. [Entity-Based Semantic Adequacy for Data-to-Text Generation](https://aclanthology.org/2021.findings-emnlp.132/) *— 2021 · Findings of the Association for Computational Linguistics: EMNLP 2021*
30. [Evaluating Multiway Multilingual NMT in the Turkic Languages](https://aclanthology.org/2021.wmt-1.60/) *— 2021 · Proceedings of the Sixth Conference on Machine Translation*
31. [Evaluating the Evaluation Metrics for Style Transfer: A Case Study in Multilingual Formality Transfer](https://md.mova.elamur.ai/free/en/docs/papers/briakou-2021-evaluating-evaluation-metrics-style-transfer/) *— our card · 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing*
32. [Evaluating the Morphosyntactic Well-formedness of Generated Texts](https://aclanthology.org/2021.emnlp-main.570/) *— 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing*
33. [EventNarrative: A large-scale Event-centric Dataset for Knowledge Graph-to-Text Generation](https://arxiv.org/abs/2111.00276) *— 2021 · arXiv:2111.00276*
34. [Experts, Errors, and Context: A Large-Scale Study of Human Evaluation for Machine Translation](https://md.mova.elamur.ai/free/en/docs/papers/freitag-2021-experts-errors-context-large-scale/) *— our card · 2021*
35. [Extremely low-resource machine translation for closely related languages](https://aclanthology.org/2021.nodalida-main.5/) *— 2021 · Proceedings of the 23rd Nordic Conference on Computational Linguistics (NoDaLiDa)*
36. [Few-shot Knowledge Graph-to-Text Generation with Pretrained Language Models](https://aclanthology.org/2021.findings-acl.136/) *— 2021 · Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021*
37. [Findings of the AmericasNLP 2021 Shared Task on Open Machine Translation for Indigenous Languages of the Americas](https://aclanthology.org/2021.americasnlp-1.23/) *— 2021 · Proceedings of the First Workshop on Natural Language Processing for Indigenous Languages of the Americas*
38. [Findings of the LoResMT 2021 Shared Task on COVID and Sign Language for Low-resource Languages](https://aclanthology.org/2021.mtsummit-loresmt.11/) *— 2021 · Proceedings of the 4th Workshop on Technologies for MT of Low Resource Languages (LoResMT2021)*
39. [Findings of the WMT 2021 Shared Tasks in Unsupervised MT and Very Low Resource Supervised MT](https://aclanthology.org/2021.wmt-1.72/) *— 2021 · Proceedings of the Sixth Conference on Machine Translation*
40. [Fine Grained Human Evaluation for English-to-Chinese Machine Translation: A Case Study on Scientific Text](https://arxiv.org/abs/2110.14766) *— 2021 · arXiv:2110.14766*
41. [Improving the Lexical Ability of Pretrained Language Models for Unsupervised Neural Machine Translation](https://aclanthology.org/2021.naacl-main.16/) *— 2021 · Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies*
42. [Investigating Pretrained Language Models for Graph-to-Text Generation](https://aclanthology.org/2021.nlp4convai-1.20/) *— 2021 · Proceedings of the 3rd Workshop on Natural Language Processing for Conversational AI*
43. [Just Ask! Evaluating Machine Translation by Asking and Answering Questions](https://aclanthology.org/2021.wmt-1.58/) *— 2021 · Proceedings of the Sixth Conference on Machine Translation*
44. [MMTAfrica: Multilingual Machine Translation for African Languages](https://aclanthology.org/2021.wmt-1.48/) *— 2021 · Proceedings of the Sixth Conference on Machine Translation*
45. [MTEQA at WMT21 Metrics Shared Task](https://aclanthology.org/2021.wmt-1.110/) *— 2021 · Proceedings of the Sixth Conference on Machine Translation*
46. [Machine Translation in the Covid domain: an English-Irish case study for LoResMT 2021](https://aclanthology.org/2021.mtsummit-loresmt.15/) *— 2021 · Proceedings of the 4th Workshop on Technologies for MT of Low Resource Languages (LoResMT2021)*
47. [Macro-Average: Rare Types Are Important Too](https://aclanthology.org/2021.naacl-main.90/) *— 2021 · Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies*
48. [Multilingual Domain Adaptation for NMT: Decoupling Language and Domain Information with Adapters](https://aclanthology.org/2021.wmt-1.64/) *— 2021 · Proceedings of the Sixth Conference on Machine Translation*
49. [Multilingual Unsupervised Neural Machine Translation with Denoising Adapters](https://aclanthology.org/2021.emnlp-main.533/) *— 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing*
50. [NRC-CNRC Machine Translation Systems for the 2021 AmericasNLP Shared Task](https://aclanthology.org/2021.americasnlp-1.25/) *— 2021 · Proceedings of the First Workshop on Natural Language Processing for Indigenous Languages of the Americas*
51. [NRC-CNRC Systems for Upper Sorbian-German and Lower Sorbian-German Machine Translation 2021](https://aclanthology.org/2021.wmt-1.107/) *— 2021 · Proceedings of the Sixth Conference on Machine Translation*
52. [Neural Machine Translation Quality and Post-Editing Performance](https://aclanthology.org/2021.emnlp-main.801/) *— 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing*
53. [On the Usability of Transformers-based Models for a French Question-Answering Task](https://aclanthology.org/2021.ranlp-1.29/) *— 2021 · Proceedings of the International Conference on Recent Advances in Natural Language Processing (RANLP 2021)*
54. [Peru is Multilingual, Its Machine Translation Should Be Too?](https://aclanthology.org/2021.americasnlp-1.22/) *— 2021 · Proceedings of the First Workshop on Natural Language Processing for Indigenous Languages of the Americas*
55. [Pruning Neural Machine Translation for Speed Using Group Lasso](https://aclanthology.org/2021.wmt-1.116/) *— 2021 · Proceedings of the Sixth Conference on Machine Translation*
56. [Results of the WMT21 Metrics Shared Task: Evaluating Metrics with Expert-based Human Evaluations on TED and News Domain](https://aclanthology.org/2021.wmt-1.73/) *— 2021 · Proceedings of the Sixth Conference on Machine Translation*
57. [RoBLEURT Submission for WMT2021 Metrics Task](https://aclanthology.org/2021.wmt-1.114/) *— 2021 · Proceedings of the Sixth Conference on Machine Translation*
58. [Scientific Credibility of Machine Translation Research: A Meta-Evaluation of 769 Papers](https://aclanthology.org/2021.acl-long.566/) *— 2021 · Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers)*
59. [Smelting Gold and Silver for Improved Multilingual AMR-to-Text Generation](https://aclanthology.org/2021.emnlp-main.57/) *— 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing*
60. [Structural Adapters in Pretrained Language Models for AMR-to-Text Generation](https://aclanthology.org/2021.emnlp-main.351/) *— 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing*
61. [Structural Biases for Improving Transformers on Translation into Morphologically Rich Languages](https://aclanthology.org/2021.mtsummit-loresmt.6/) *— 2021 · Proceedings of the 4th Workshop on Technologies for MT of Low Resource Languages (LoResMT2021)*
62. [SummEval: Re-evaluating Summarization Evaluation](https://aclanthology.org/2021.tacl-1.24/) *— 2021*
63. [The Curious Case of Hallucinations in Neural Machine Translation](https://aclanthology.org/2021.naacl-main.92/) *— 2021 · Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies*
64. [The Effect of Domain and Diacritics in Yoruba–English Neural Machine Translation](https://aclanthology.org/2021.mtsummit-research.6/) *— 2021 · Proceedings of Machine Translation Summit XVIII: Research Track*
65. [The Effectiveness of Morphology-aware Segmentation in Low-Resource Neural Machine Translation](https://aclanthology.org/2021.eacl-srw.22/) *— 2021 · Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Student Research Workshop*
66. [The Eval4NLP Shared Task on Explainable Quality Estimation: Overview and Results](https://aclanthology.org/2021.eval4nlp-1.17/) *— 2021 · Proceedings of the 2nd Workshop on Evaluation and Comparison of NLP Systems*
67. [The LMU Munich System for the WMT 2021 Large-Scale Multilingual Machine Translation Shared Task](https://aclanthology.org/2021.wmt-1.49/) *— 2021 · Proceedings of the Sixth Conference on Machine Translation*
68. [The LMU Munich Systems for the WMT21 Unsupervised and Very Low-Resource Translation Task](https://aclanthology.org/2021.wmt-1.105/) *— 2021 · Proceedings of the Sixth Conference on Machine Translation*
69. [The UCF Systems for the LoResMT 2021 Machine Translation Shared Task](https://aclanthology.org/2021.mtsummit-loresmt.13/) *— 2021 · Proceedings of the 4th Workshop on Technologies for MT of Low Resource Languages (LoResMT2021)*
70. [To Ship or Not to Ship: An Extensive Evaluation of Automatic Metrics for Machine Translation](https://aclanthology.org/2021.wmt-1.57/) *— 2021 · Proceedings of the Sixth Conference on Machine Translation*
71. [Towards a Decomposable Metric for Explainable Evaluation of Text Generation from AMR](https://md.mova.elamur.ai/free/en/docs/papers/opitz-2021-decomposable-metric-explainable-evaluation-text/) *— our card · 2021 · Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume*
72. [Transformers for Low-Resource Languages: Is Féidir Linn!](https://aclanthology.org/2021.mtsummit-research.5/) *— 2021 · Proceedings of Machine Translation Summit XVIII: Research Track*
73. [Uncertainty-Aware Machine Translation Evaluation](https://aclanthology.org/2021.findings-emnlp.330/) *— 2021 · Findings of the Association for Computational Linguistics: EMNLP 2021*
74. [Understanding the Impact of UGC Specificities on Translation Quality](https://aclanthology.org/2021.wnut-1.22/) *— 2021 · Proceedings of the Seventh Workshop on Noisy User-generated Text (W-NUT 2021)*
75. [Visualizing Cross-Lingual Discourse Relations in Multilingual TED Corpora](https://aclanthology.org/2021.codi-main.16/) *— 2021 · Proceedings of the 2nd Workshop on Computational Approaches to Discourse*
76. [When is Char Better Than Subword: A Systematic Study of Segmentation Algorithms for Neural Machine Translation](https://aclanthology.org/2021.acl-short.69/) *— 2021 · Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 2: Short Papers)*
77. [融合XLM词语表示的神经机器译文自动评价方法(Neural Automatic Evaluation of Machine Translation Method Combined with XLM Word Representation)](https://aclanthology.org/2021.ccl-1.2/) *— 2021 · Proceedings of the 20th Chinese National Conference on Computational Linguistics*
78. [A General Benchmarking Framework for Text Generation](https://aclanthology.org/2020.webnlg-1.3/) *— 2020 · Proceedings of the 3rd International Workshop on Natural Language Generation from the Semantic Web (WebNLG+)*
79. [A Resource for Computational Experiments on Mapudungun](https://aclanthology.org/2020.lrec-1.350/) *— 2020 · Proceedings of the Twelfth Language Resources and Evaluation Conference*
80. [A human evaluation of English-Irish statistical and neural machine translation](https://aclanthology.org/2020.eamt-1.46/) *— 2020 · Proceedings of the 22nd Annual Conference of the European Association for Machine Translation*
81. [An Error-based Investigation of Statistical and Neural Machine Translation Performance on Hindi-to-Tamil and English-to-Tamil](https://aclanthology.org/2020.wat-1.22/) *— 2020 · Proceedings of the 7th Workshop on Asian Translation*
82. [Aspects of Terminological and Named Entity Knowledge within Rule-Based Machine Translation Models for Under-Resourced Neural Machine Translation Scenarios](https://arxiv.org/abs/2009.13398) *— 2020 · arXiv:2009.13398*
83. [Automatic Machine Translation Evaluation in Many Languages via Zero-Shot Paraphrasing](https://aclanthology.org/2020.emnlp-main.8/) *— 2020 · Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)*
84. [BLEU might be Guilty but References are not Innocent](https://aclanthology.org/2020.emnlp-main.5/) *— 2020 · Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)*
85. [Can Automatic Post-Editing Improve NMT?](https://aclanthology.org/2020.emnlp-main.217/) *— 2020 · Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)*
86. [Character-level Transformer-based Neural Machine Translation](https://arxiv.org/abs/2005.11239) *— 2020 · arXiv:2005.11239*
87. [Denoising Pre-Training and Data Augmentation Strategies for Enhanced RDF Verbalization with Transformers](https://aclanthology.org/2020.webnlg-1.9/) *— 2020 · Proceedings of the 3rd International Workshop on Natural Language Generation from the Semantic Web (WebNLG+)*
88. [Detecting Non-literal Translations by Fine-tuning Cross-lingual Pre-trained Language Models](https://aclanthology.org/2020.coling-main.522/) *— 2020 · Proceedings of the 28th International Conference on Computational Linguistics*
89. [Fairseq S2T: Fast Speech-to-Text Modeling with Fairseq](https://aclanthology.org/2020.aacl-demo.6/) *— 2020 · Proceedings of the 1st Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics and the 10th International Joint Conference on Natural Language Processing: System Demonstrations*
90. [Findings of the WMT 2020 Biomedical Translation Shared Task: Basque, Italian and Russian as New Additional Languages](https://aclanthology.org/2020.wmt-1.76/) *— 2020 · Proceedings of the Fifth Conference on Machine Translation*
91. [Heterogeneous Graph Transformer for Graph-to-Sequence Learning](https://aclanthology.org/2020.acl-main.640/) *— 2020 · Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics*
92. [It's Morphin' Time! Combating Linguistic Discrimination with Inflectional Perturbations](https://aclanthology.org/2020.acl-main.263/) *— 2020 · Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics*
93. [MOCHA: A Dataset for Training and Evaluating Generative Reading Comprehension Metrics](https://aclanthology.org/2020.emnlp-main.528/) *— 2020 · Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)*
94. [Machine Translation for English–Inuktitut with Segmentation, Data Acquisition and Pre-Training](https://aclanthology.org/2020.wmt-1.29/) *— 2020 · Proceedings of the Fifth Conference on Machine Translation*
95. [Multi-Hypothesis Machine Translation Evaluation](https://aclanthology.org/2020.acl-main.113/) *— 2020 · Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics*
96. [Multiword Expression aware Neural Machine Translation](https://aclanthology.org/2020.lrec-1.471/) *— 2020 · Proceedings of the Twelfth Language Resources and Evaluation Conference*
97. [NMT and PBSMT Error Analyses in English to Brazilian Portuguese Automatic Translations](https://aclanthology.org/2020.lrec-1.446/) *— 2020 · Proceedings of the Twelfth Language Resources and Evaluation Conference*
98. [NRC Systems for the 2020 Inuktitut-English News Translation Task](https://aclanthology.org/2020.wmt-1.13/) *— 2020 · Proceedings of the Fifth Conference on Machine Translation*
99. [Neural Machine Translation for Extremely Low-Resource African Languages: A Case Study on Bambara](https://aclanthology.org/2020.loresmt-1.3/) *— 2020 · Proceedings of the 3rd Workshop on Technologies for MT of Low Resource Languages*
100. [Neural Machine Translation for translating into Croatian and Serbian](https://aclanthology.org/2020.vardial-1.10/) *— 2020 · Proceedings of the 7th Workshop on NLP for Similar Languages, Varieties and Dialects*

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