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# Who cites «A Study of Translation Edit Rate with Targeted Human Annotation» · page 3

1514 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/snover-2006-study-translation-edit-rate-targeted/)

Pages: [1](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/snover-2006-study-translation-edit-rate-targeted/) · [2](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/snover-2006-study-translation-edit-rate-targeted-2/) · **3** · [4](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/snover-2006-study-translation-edit-rate-targeted-4/) · [5](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/snover-2006-study-translation-edit-rate-targeted-5/) · [6](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/snover-2006-study-translation-edit-rate-targeted-6/) · [7](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/snover-2006-study-translation-edit-rate-targeted-7/) · [8](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/snover-2006-study-translation-edit-rate-targeted-8/) · [9](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/snover-2006-study-translation-edit-rate-targeted-9/) · [10](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/snover-2006-study-translation-edit-rate-targeted-10/) · [11](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/snover-2006-study-translation-edit-rate-targeted-11/) · [12](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/snover-2006-study-translation-edit-rate-targeted-12/) · [13](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/snover-2006-study-translation-edit-rate-targeted-13/) · [14](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/snover-2006-study-translation-edit-rate-targeted-14/) · [15](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/snover-2006-study-translation-edit-rate-targeted-15/) · [16](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/snover-2006-study-translation-edit-rate-targeted-16/)

1. [Machine translation of Korean statutes examined from the perspective of quality and productivity](https://aclanthology.org/2023.mtsummit-users.13/) *— 2023 · Proceedings of Machine Translation Summit XIX, Vol. 2: Users Track*
2. [Neural Machine Translation Methods for Translating Text to Sign Language Glosses](https://aclanthology.org/2023.acl-long.700/) *— 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
3. [On Search Strategies for Document-Level Neural Machine Translation](https://aclanthology.org/2023.findings-acl.811/) *— 2023 · Findings of the Association for Computational Linguistics: ACL 2023*
4. [On Uncertainty Calibration and Selective Generation in Probabilistic Neural Summarization: A Benchmark Study](https://aclanthology.org/2023.findings-emnlp.197/) *— 2023 · Findings of the Association for Computational Linguistics: EMNLP 2023*
5. [PE effort and neural-based automatic MT metrics: do they correlate?](https://aclanthology.org/2023.eamt-1.31/) *— 2023 · Proceedings of the 24th Annual Conference of the European Association for Machine Translation*
6. [Perturbation-based QE: An Explainable, Unsupervised Word-level Quality Estimation Method for Blackbox Machine Translation](https://aclanthology.org/2023.mtsummit-research.6/) *— 2023 · Proceedings of Machine Translation Summit XIX, Vol. 1: Research Track*
7. [Physician Detection of Clinical Harm in Machine Translation: Quality Estimation Aids in Reliance and Backtranslation Identifies Critical Errors](https://aclanthology.org/2023.emnlp-main.712/) *— 2023 · Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing*
8. [Poor Man''s Quality Estimation: Predicting Reference-Based MT Metrics Without the Reference](https://aclanthology.org/2023.eacl-main.95/) *— 2023 · Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics*
9. [PromptST: Abstract Prompt Learning for End-to-End Speech Translation](https://aclanthology.org/2023.emnlp-main.627/) *— 2023 · Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing*
10. [Quality Estimation-Assisted Automatic Post-Editing](https://aclanthology.org/2023.findings-emnlp.115/) *— 2023 · Findings of the Association for Computational Linguistics: EMNLP 2023*
11. [Reference Free Domain Adaptation for Translation of Noisy Questions with Question Specific Rewards](https://aclanthology.org/2023.findings-emnlp.16/) *— 2023 · Findings of the Association for Computational Linguistics: EMNLP 2023*
12. [Reference Matters: Benchmarking Factual Error Correction for Dialogue Summarization with Fine-grained Evaluation Framework](https://aclanthology.org/2023.acl-long.779/) *— 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
13. [Rethinking Round-Trip Translation for Machine Translation Evaluation](https://aclanthology.org/2023.findings-acl.22/) *— 2023 · Findings of the Association for Computational Linguistics: ACL 2023*
14. [Rethinking the Word-level Quality Estimation for Machine Translation from Human Judgement](https://aclanthology.org/2023.findings-acl.126/) *— 2023 · Findings of the Association for Computational Linguistics: ACL 2023*
15. [SESCORE2: Learning Text Generation Evaluation via Synthesizing Realistic Mistakes](https://aclanthology.org/2023.acl-long.283/) *— 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
16. [Songs Across Borders: Singable and Controllable Neural Lyric Translation](https://aclanthology.org/2023.acl-long.27/) *— 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
17. [TARJAMAT: Evaluation of Bard and ChatGPT on Machine Translation of Ten Arabic Varieties](https://aclanthology.org/2023.arabicnlp-1.6/) *— 2023 · Proceedings of ArabicNLP 2023*
18. [Tailoring Domain Adaptation for Machine Translation Quality Estimation](https://aclanthology.org/2023.eamt-1.2/) *— 2023 · Proceedings of the 24th Annual Conference of the European Association for Machine Translation*
19. [Test-time Adaptation for Machine Translation Evaluation by Uncertainty Minimization](https://aclanthology.org/2023.acl-long.47/) *— 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
20. [Tokengram_F, a Fast and Accurate Token-based chrF++ Derivative](https://aclanthology.org/2023.wmt-1.59/) *— 2023 · Proceedings of the Eighth Conference on Machine Translation*
21. [Toward Human-Like Evaluation for Natural Language Generation with Error Analysis](https://aclanthology.org/2023.acl-long.324/) *— 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
22. [Training and Meta-Evaluating Machine Translation Evaluation Metrics at the Paragraph Level](https://aclanthology.org/2023.wmt-1.96/) *— 2023 · Proceedings of the Eighth Conference on Machine Translation*
23. [Unsupervised Translation Quality Estimation Exploiting Synthetic Data and Pre-trained Multilingual Encoder](https://arxiv.org/abs/2311.05117) *— 2023 · arXiv:2311.05117*
24. [Using Large Language Models for Zero-Shot Natural Language Generation from Knowledge Graphs](https://aclanthology.org/2023.mmnlg-1.5/) *— 2023 · Proceedings of the Workshop on Multimodal, Multilingual Natural Language Generation and Multilingual WebNLG Challenge (MM-NLG 2023)*
25. [VERVE: Template-based ReflectiVE Rewriting for MotiVational IntErviewing](https://aclanthology.org/2023.findings-emnlp.690/) *— 2023 · Findings of the Association for Computational Linguistics: EMNLP 2023*
26. [VisText: A Benchmark for Semantically Rich Chart Captioning](https://aclanthology.org/2023.acl-long.401/) *— 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
27. [f-Divergence Minimization for Sequence-Level Knowledge Distillation](https://aclanthology.org/2023.acl-long.605/) *— 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
28. [(Psycho-)Linguistic Features Meet Transformer Models for Improved Explainable and Controllable Text Simplification](https://aclanthology.org/2022.tsar-1.12/) *— 2022 · Proceedings of the Workshop on Text Simplification, Accessibility, and Readability (TSAR-2022)*
29. [A Quality Estimation and Quality Evaluation Tool for the Translation Industry](https://aclanthology.org/2022.eamt-1.43/) *— 2022 · Proceedings of the 23rd Annual Conference of the European Association for Machine Translation*
30. [A Template-based Method for Constrained Neural Machine Translation](https://aclanthology.org/2022.emnlp-main.240/) *— 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing*
31. [A large-scale computational study of content preservation measures for text style transfer and paraphrase generation](https://aclanthology.org/2022.acl-srw.23/) *— 2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics: Student Research Workshop*
32. [An Overview on Machine Translation Evaluation](https://arxiv.org/abs/2202.11027) *— 2022 · arXiv:2202.11027*
33. [Approaching English-Polish Machine Translation Quality Assessment with Neural-based Methods](https://arxiv.org/abs/2209.11016) *— 2022 · arXiv:2209.11016 · Proceedings of the PolEval 2021 Workshop, 2021, 73-78*
34. [Bidimensional Leaderboards: Generate and Evaluate Language Hand in Hand](https://aclanthology.org/2022.naacl-main.259/) *— 2022 · Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies*
35. [BitextEdit: Automatic Bitext Editing for Improved Low-Resource Machine Translation](https://aclanthology.org/2022.findings-naacl.110/) *— 2022 · Findings of the Association for Computational Linguistics: NAACL 2022*
36. [BlonDe: An Automatic Evaluation Metric for Document-level Machine Translation](https://aclanthology.org/2022.naacl-main.111/) *— 2022 · Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies*
37. [CometKiwi: IST-Unbabel 2022 Submission for the Quality Estimation Shared Task](https://aclanthology.org/2022.wmt-1.60/) *— 2022 · Proceedings of the Seventh Conference on Machine Translation (WMT)*
38. [ConsistTL: Modeling Consistency in Transfer Learning for Low-Resource Neural Machine Translation](https://aclanthology.org/2022.emnlp-main.574/) *— 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing*
39. [DEMETR: Diagnosing Evaluation Metrics for Translation](https://aclanthology.org/2022.emnlp-main.649/) *— 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing*
40. [DivEMT: Neural Machine Translation Post-Editing Effort Across Typologically Diverse Languages](https://aclanthology.org/2022.emnlp-main.532/) *— 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing*
41. [Domain Adaptation in Neural Machine Translation using a Qualia-Enriched FrameNet](https://aclanthology.org/2022.lrec-1.1/) *— 2022 · Proceedings of the Thirteenth Language Resources and Evaluation Conference*
42. [Domain-Specific Text Generation for Machine Translation](https://aclanthology.org/2022.amta-research.2/) *— 2022 · Proceedings of the 15th biennial conference of the Association for Machine Translation in the Americas (Volume 1: Research Track)*
43. [EdiT5: Semi-Autoregressive Text Editing with T5 Warm-Start](https://aclanthology.org/2022.findings-emnlp.156/) *— 2022 · Findings of the Association for Computational Linguistics: EMNLP 2022*
44. [Embarrassingly Easy Document-Level MT Metrics: How to Convert Any Pretrained Metric into a Document-Level Metric](https://aclanthology.org/2022.wmt-1.6/) *— 2022 · Proceedings of the Seventh Conference on Machine Translation (WMT)*
45. [Evaluating Subtitle Segmentation for End-to-end Generation Systems](https://aclanthology.org/2022.lrec-1.328/) *— 2022 · Proceedings of the Thirteenth Language Resources and Evaluation Conference*
46. [Finding Memo: Extractive Memorization in Constrained Sequence Generation Tasks](https://aclanthology.org/2022.findings-emnlp.378/) *— 2022 · Findings of the Association for Computational Linguistics: EMNLP 2022*
47. [Findings of the WMT 2022 Shared Task on Automatic Post-Editing](https://aclanthology.org/2022.wmt-1.5/) *— 2022 · Proceedings of the Seventh Conference on Machine Translation (WMT)*
48. [Findings of the WMT 2022 Shared Task on Quality Estimation](https://aclanthology.org/2022.wmt-1.3/) *— 2022 · Proceedings of the Seventh Conference on Machine Translation (WMT)*
49. [Generation of Patient After-Visit Summaries to Support Physicians](https://aclanthology.org/2022.coling-1.544/) *— 2022 · Proceedings of the 29th International Conference on Computational Linguistics*
50. [HOPE: A Task-Oriented and Human-Centric Evaluation Framework Using Professional Post-Editing Towards More Effective MT Evaluation](https://aclanthology.org/2022.lrec-1.2/) *— 2022 · Proceedings of the Thirteenth Language Resources and Evaluation Conference*
51. [HilMeMe: A Human-in-the-Loop Machine Translation Evaluation Metric Looking into Multi-Word Expressions](https://arxiv.org/abs/2211.05201) *— 2022 · arXiv:2211.05201*
52. [IIT Bombay's WMT22 Automatic Post-Editing Shared Task Submission](https://aclanthology.org/2022.wmt-1.67/) *— 2022 · Proceedings of the Seventh Conference on Machine Translation (WMT)*
53. [Improving Neural Machine Translation with the Abstract Meaning Representation by Combining Graph and Sequence Transformers](https://aclanthology.org/2022.dlg4nlp-1.2/) *— 2022 · Proceedings of the 2nd Workshop on Deep Learning on Graphs for Natural Language Processing (DLG4NLP 2022)*
54. [Investigating Data Variance in Evaluations of Automatic Machine Translation Metrics](https://aclanthology.org/2022.findings-acl.14/) *— 2022 · Findings of the Association for Computational Linguistics: ACL 2022*
55. [Is Encoder-Decoder Redundant for Neural Machine Translation?](https://aclanthology.org/2022.aacl-main.43/) *— 2022 · Proceedings of the 2nd Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics and the 12th International Joint Conference on Natural Language Processing (Volume 1: Long Papers)*
56. [Knowledge Distillation for Sustainable Neural Machine Translation](https://aclanthology.org/2022.amta-upg.16/) *— 2022 · Proceedings of the 15th Biennial Conference of the Association for Machine Translation in the Americas (Volume 2: Users and Providers Track and Government Track)*
57. [Linguistically-Motivated Yorùbá-English Machine Translation](https://aclanthology.org/2022.coling-1.449/) *— 2022 · Proceedings of the 29th International Conference on Computational Linguistics*
58. [Literary translation as a three-stage process: machine translation, post-editing and revision](https://aclanthology.org/2022.eamt-1.13/) *— 2022 · Proceedings of the 23rd Annual Conference of the European Association for Machine Translation*
59. [MS-COMET: More and Better Human Judgements Improve Metric Performance](https://aclanthology.org/2022.wmt-1.47/) *— 2022 · Proceedings of the Seventh Conference on Machine Translation (WMT)*
60. [MSCTD: A Multimodal Sentiment Chat Translation Dataset](https://aclanthology.org/2022.acl-long.186/) *— 2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
61. [MaTESe: Machine Translation Evaluation as a Sequence Tagging Problem](https://aclanthology.org/2022.wmt-1.51/) *— 2022 · Proceedings of the Seventh Conference on Machine Translation (WMT)*
62. [Mismatching-Aware Unsupervised Translation Quality Estimation For Low-Resource Languages](https://arxiv.org/abs/2208.00463) *— 2022 · arXiv:2208.00463*
63. [Multi-Granularity Optimization for Non-Autoregressive Translation](https://aclanthology.org/2022.emnlp-main.339/) *— 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing*
64. [Multilingual Abstract Meaning Representation for Celtic Languages](https://aclanthology.org/2022.cltw-1.1/) *— 2022 · Proceedings of the 4th Celtic Language Technology Workshop within LREC2022*
65. [NJUNLP's Participation for the WMT2022 Quality Estimation Shared Task](https://aclanthology.org/2022.wmt-1.57/) *— 2022 · Proceedings of the Seventh Conference on Machine Translation (WMT)*
66. [NLG-Metricverse: An End-to-End Library for Evaluating Natural Language Generation](https://aclanthology.org/2022.coling-1.306/) *— 2022 · Proceedings of the 29th International Conference on Computational Linguistics*
67. [Non-Autoregressive Neural Machine Translation: A Call for Clarity](https://aclanthology.org/2022.emnlp-main.179/) *— 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing*
68. [Not All Errors are Equal: Learning Text Generation Metrics using Stratified Error Synthesis](https://aclanthology.org/2022.findings-emnlp.489/) *— 2022 · Findings of the Association for Computational Linguistics: EMNLP 2022*
69. [Novelty Controlled Paraphrase Generation with Retrieval Augmented Conditional Prompt Tuning](https://arxiv.org/abs/2202.00535) *— 2022 · arXiv:2202.00535*
70. [On Assessing and Developing Spoken `Grammatical Error Correction' Systems](https://aclanthology.org/2022.bea-1.9/) *— 2022 · Proceedings of the 17th Workshop on Innovative Use of NLP for Building Educational Applications (BEA 2022)*
71. [Original or Translated? On the Use of Parallel Data for Translation Quality Estimation](https://arxiv.org/abs/2212.10257) *— 2022 · arXiv:2212.10257*
72. [Part Represents Whole: Improving the Evaluation of Machine Translation System Using Entropy Enhanced Metrics](https://aclanthology.org/2022.findings-aacl.28/) *— 2022 · Findings of the Association for Computational Linguistics: AACL-IJCNLP 2022*
73. [Passing Parser Uncertainty to the Transformer: Labeled Dependency Distributions for Neural Machine Translation](https://aclanthology.org/2022.eamt-1.7/) *— 2022 · Proceedings of the 23rd Annual Conference of the European Association for Machine Translation*
74. [PreQuEL: Quality Estimation of Machine Translation Outputs in Advance](https://aclanthology.org/2022.emnlp-main.767/) *— 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing*
75. [Pretrained Speech Encoders and Efficient Fine-tuning Methods for Speech Translation: UPC at IWSLT 2022](https://aclanthology.org/2022.iwslt-1.23/) *— 2022 · Proceedings of the 19th International Conference on Spoken Language Translation (IWSLT 2022)*
76. [QUAK: A Synthetic Quality Estimation Dataset for Korean-English Neural Machine Translation](https://aclanthology.org/2022.coling-1.460/) *— 2022 · Proceedings of the 29th International Conference on Computational Linguistics*
77. [R2D2: Robust Data-to-Text with Replacement Detection](https://aclanthology.org/2022.emnlp-main.464/) *— 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing*
78. [Rethink about the Word-level Quality Estimation for Machine Translation from Human Judgement](https://arxiv.org/abs/2209.05695) *— 2022 · arXiv:2209.05695*
79. [Revision for Concision: A Constrained Paraphrase Generation Task](https://aclanthology.org/2022.tsar-1.6/) *— 2022 · Proceedings of the Workshop on Text Simplification, Accessibility, and Readability (TSAR-2022)*
80. [Robust MT Evaluation with Sentence-level Multilingual Augmentation](https://aclanthology.org/2022.wmt-1.43/) *— 2022 · Proceedings of the Seventh Conference on Machine Translation (WMT)*
81. [Scheduled Multi-task Learning for Neural Chat Translation](https://aclanthology.org/2022.acl-long.300/) *— 2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
82. [Self-supervised Graph Masking Pre-training for Graph-to-Text Generation](https://aclanthology.org/2022.emnlp-main.321/) *— 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing*
83. [Semantic Similarity Based Filtering for Turkish Paraphrase Dataset Creation](https://aclanthology.org/2022.icnlsp-1.14/) *— 2022 · Proceedings of the 5th International Conference on Natural Language and Speech Processing (ICNLSP 2022)*
84. [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)*
85. [The Ecological Footprint of Neural Machine Translation Systems](https://arxiv.org/abs/2202.02170) *— 2022 · arXiv:2202.02170*
86. [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)*
87. [Towards Making the Most of Pre-trained Translation Model for Quality Estimation](https://aclanthology.org/2022.ccl-1.77/) *— 2022 · Proceedings of the 21st Chinese National Conference on Computational Linguistics*
88. [Translating Spanish into Spanish Sign Language: Combining Rules and Data-driven Approaches](https://aclanthology.org/2022.loresmt-1.10/) *— 2022 · Proceedings of the Fifth Workshop on Technologies for Machine Translation of Low-Resource Languages (LoResMT 2022)*
89. [Translation Error Detection as Rationale Extraction](https://aclanthology.org/2022.findings-acl.327/) *— 2022 · Findings of the Association for Computational Linguistics: ACL 2022*
90. [Understanding Metrics for Paraphrasing](https://arxiv.org/abs/2205.13119) *— 2022 · arXiv:2205.13119*
91. [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)*
92. [Using Pre-Trained Language Models for Producing Counter Narratives Against Hate Speech: a Comparative Study](https://aclanthology.org/2022.findings-acl.245/) *— 2022 · Findings of the Association for Computational Linguistics: ACL 2022*
93. [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*
94. [WeTS: A Benchmark for Translation Suggestion](https://aclanthology.org/2022.emnlp-main.353/) *— 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing*
95. [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)*
96. [Who Are We Talking About? Handling Person Names in Speech Translation](https://aclanthology.org/2022.iwslt-1.6/) *— 2022 · Proceedings of the 19th International Conference on Spoken Language Translation (IWSLT 2022)*
97. [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*
98. [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*
99. [Adaptation of Back-translation to Automatic Post-Editing for Synthetic Data Generation](https://aclanthology.org/2021.eacl-main.322/) *— 2021 · Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume*
100. [Adapting Neural Machine Translation for Automatic Post-Editing](https://aclanthology.org/2021.wmt-1.35/) *— 2021 · Proceedings of the Sixth Conference on Machine Translation*

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