---
title: "Who cites chrF: character n-gram F-score for automatic MT…"
description: "The papers of the Elamur Research library that cite «chrF: character n-gram F-score for automatic MT evaluation», found in their bibliographies."
canonical: "https://research.elamur.ai/free/en/papers/popovic-2015-chrf-character-n-gram-f/cited-by/page/9/"
---
[Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/popovic-2015-chrf-character-n-gram-f/cited-by/page/9/)

[home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [chrF: character n-gram F-score for automatic MT…](https://md.research.elamur.ai/free/en/papers/popovic-2015-chrf-character-n-gram-f/) / cited by

# Who cites «chrF: character n-gram F-score for automatic MT evaluation» · page 9

1094 papers of our library cite it, newest first: found in their bibliographies, which we read ourselves. [← the card](https://md.research.elamur.ai/free/en/papers/popovic-2015-chrf-character-n-gram-f/)

Pages: [1](https://md.research.elamur.ai/free/en/papers/popovic-2015-chrf-character-n-gram-f/cited-by/) · … · [8](https://md.research.elamur.ai/free/en/papers/popovic-2015-chrf-character-n-gram-f/cited-by/page/8/) · **9** · [10](https://md.research.elamur.ai/free/en/papers/popovic-2015-chrf-character-n-gram-f/cited-by/page/10/) · [11](https://md.research.elamur.ai/free/en/papers/popovic-2015-chrf-character-n-gram-f/cited-by/page/11/)

1. [Automated Evaluation Metric for Terminology Consistency in MT](https://aclanthology.org/2022.wmt-1.41/) *— 2022 · Proceedings of the Seventh Conference on Machine Translation (WMT)*
2. [Automatic Normalisation of Early Modern French](https://aclanthology.org/2022.lrec-1.358/) *— 2022 · Proceedings of the Thirteenth Language Resources and Evaluation Conference*
3. [BERTScore is Unfair: On Social Bias in Language Model-Based Metrics for Text Generation](https://aclanthology.org/2022.emnlp-main.245/) *— 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing*
4. [BPE beyond Word Boundary: How NOT to use Multi Word Expressions in Neural Machine Translation](https://aclanthology.org/2022.insights-1.24/) *— 2022 · Proceedings of the Third Workshop on Insights from Negative Results in NLP*
5. [BPE vs. Morphological Segmentation: A Case Study on Machine Translation of Four Polysynthetic Languages](https://aclanthology.org/2022.findings-acl.78/) *— 2022 · Findings of the Association for Computational Linguistics: ACL 2022*
6. [Benchmarking Azerbaijani Neural Machine Translation](https://arxiv.org/abs/2207.14473) *— 2022 · arXiv:2207.14473*
7. [Benefiting from Language Similarity in the Multilingual MT Training: Case Study of Indonesian and Malaysian](https://aclanthology.org/2022.loresmt-1.11/) *— 2022 · Proceedings of the Fifth Workshop on Technologies for Machine Translation of Low-Resource Languages (LoResMT 2022)*
8. [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*
9. [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*
10. [Byte-based Multilingual NMT for Endangered Languages](https://aclanthology.org/2022.coling-1.388/) *— 2022 · Proceedings of the 29th International Conference on Computational Linguistics*
11. [COMET-22: Unbabel-IST 2022 Submission for the Metrics Shared Task](https://aclanthology.org/2022.wmt-1.52/) *— 2022 · Proceedings of the Seventh Conference on Machine Translation (WMT)*
12. [Can We Use Word Embeddings for Enhancing Guarani-Spanish Machine Translation?](https://aclanthology.org/2022.computel-1.16/) *— 2022 · Proceedings of the Fifth Workshop on the Use of Computational Methods in the Study of Endangered Languages*
13. [Comparing and combining tagging with different decoding algorithms for back-translation in NMT: learnings from a low resource scenario](https://aclanthology.org/2022.eamt-1.6/) *— 2022 · Proceedings of the 23rd Annual Conference of the European Association for Machine Translation*
14. [Competency-Aware Neural Machine Translation: Can Machine Translation Know its Own Translation Quality?](https://aclanthology.org/2022.emnlp-main.330/) *— 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing*
15. [DEEP: DEnoising Entity Pre-training for Neural Machine Translation](https://aclanthology.org/2022.acl-long.123/) *— 2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
16. [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*
17. [DaLC: Domain Adaptation Learning Curve Prediction for Neural Machine Translation](https://aclanthology.org/2022.findings-acl.141/) *— 2022 · Findings of the Association for Computational Linguistics: ACL 2022*
18. [Deep Learning for Text Style Transfer: A Survey](https://aclanthology.org/2022.cl-1.6/) *— 2022 · Computational Linguistics*
19. [Detecting Languages Unintelligible to Multilingual Models through Local Structure Probes](https://aclanthology.org/2022.findings-emnlp.393/) *— 2022 · Findings of the Association for Computational Linguistics: EMNLP 2022*
20. [DialSummEval: Revisiting Summarization Evaluation for Dialogues](https://aclanthology.org/2022.naacl-main.418/) *— 2022 · Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies*
21. [Digging Errors in NMT: Evaluating and Understanding Model Errors from Partial Hypothesis Space](https://aclanthology.org/2022.emnlp-main.827/) *— 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing*
22. [Disentangling Uncertainty in Machine Translation Evaluation](https://aclanthology.org/2022.emnlp-main.591/) *— 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing*
23. [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*
24. [Does partial pretranslation can improve low ressourced-languages pairs?](https://aclanthology.org/2022.wat-1.10/) *— 2022 · Proceedings of the 9th Workshop on Asian Translation*
25. [ERNIE-Code: Beyond English-Centric Cross-lingual Pretraining for Programming Languages](https://arxiv.org/abs/2212.06742) *— 2022 · arXiv:2212.06742*
26. [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)*
27. [Empirical Evaluation of Language Agnostic Filtering of Parallel Data for Low Resource Languages](https://aclanthology.org/2022.paclic-1.38/) *— 2022 · Proceedings of the 36th Pacific Asia Conference on Language, Information and Computation*
28. [Enabling arbitrary translation objectives with Adaptive Tree Search](https://arxiv.org/abs/2202.11444) *— 2022 · arXiv:2202.11444*
29. [English-Russian Data Augmentation for Neural Machine Translation](https://aclanthology.org/2022.amta-coco4mt.1/) *— 2022 · Proceedings of the 15th biennial conference of the Association for Machine Translation in the Americas (Workshop 2: Corpus Generation and Corpus Augmentation for Machine Translation)*
30. [Evaluating Machine Translation in Cross-lingual E-Commerce Search](https://aclanthology.org/2022.amta-research.25/) *— 2022 · Proceedings of the 15th biennial conference of the Association for Machine Translation in the Americas (Volume 1: Research Track)*
31. [Evaluating Pre-training Objectives for Low-Resource Translation into Morphologically Rich Languages](https://aclanthology.org/2022.lrec-1.527/) *— 2022 · Proceedings of the Thirteenth Language Resources and Evaluation Conference*
32. [Exploring Robustness of Machine Translation Metrics: A Study of Twenty-Two Automatic Metrics in the WMT22 Metric Task](https://aclanthology.org/2022.wmt-1.46/) *— 2022 · Proceedings of the Seventh Conference on Machine Translation (WMT)*
33. [Exploring diversity in back translation for low-resource machine translation](https://aclanthology.org/2022.deeplo-1.8/) *— 2022 · Proceedings of the Third Workshop on Deep Learning for Low-Resource Natural Language Processing*
34. [Few-shot fine-tuning SOTA summarization models for medical dialogues](https://aclanthology.org/2022.naacl-srw.32/) *— 2022 · Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies: Student Research Workshop*
35. [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*
36. [Findings of the 2022 Conference on Machine Translation (WMT22)](https://aclanthology.org/2022.wmt-1.1/) *— 2022 · Proceedings of the Seventh Conference on Machine Translation (WMT)*
37. [Findings of the First WMT Shared Task on Sign Language Translation (WMT-SLT22)](https://aclanthology.org/2022.wmt-1.71/) *— 2022 · Proceedings of the Seventh Conference on Machine Translation (WMT)*
38. [Findings of the IWSLT 2022 Evaluation Campaign](https://aclanthology.org/2022.iwslt-1.10/) *— 2022 · Proceedings of the 19th International Conference on Spoken Language Translation (IWSLT 2022)*
39. [Findings of the WMT 2022 Shared Task on Chat Translation](https://aclanthology.org/2022.wmt-1.70/) *— 2022 · Proceedings of the Seventh Conference on Machine Translation (WMT)*
40. [From COMET to COMES – Can Summary Evaluation Benefit from Translation Evaluation?](https://aclanthology.org/2022.eval4nlp-1.3/) *— 2022 · Proceedings of the 3rd Workshop on Evaluation and Comparison of NLP Systems*
41. [Graph-to-Text Generation with Dynamic Structure Pruning](https://aclanthology.org/2022.coling-1.534/) *— 2022 · Proceedings of the 29th International Conference on Computational Linguistics*
42. [HW-TSC Translation Systems for the WMT22 Biomedical Translation Task](https://aclanthology.org/2022.wmt-1.88/) *— 2022 · Proceedings of the Seventh Conference on Machine Translation (WMT)*
43. [HW-TSC's Submissions to the WMT 2022 General Machine Translation Shared Task](https://aclanthology.org/2022.wmt-1.36/) *— 2022 · Proceedings of the Seventh Conference on Machine Translation (WMT)*
44. [High Quality Rather than High Model Probability: Minimum Bayes Risk Decoding with Neural Metrics](https://aclanthology.org/2022.tacl-1.47/) *— 2022 · Transactions of the Association for Computational Linguistics*
45. [How Robust is Neural Machine Translation to Language Imbalance in Multilingual Tokenizer Training?](https://aclanthology.org/2022.amta-research.8/) *— 2022 · Proceedings of the 15th biennial conference of the Association for Machine Translation in the Americas (Volume 1: Research Track)*
46. [Human Evaluation and Correlation with Automatic Metrics in Consultation Note Generation](https://aclanthology.org/2022.acl-long.394/) *— 2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
47. [Human Judgement as a Compass to Navigate Automatic Metrics for Formality Transfer](https://aclanthology.org/2022.humeval-1.9/) *— 2022 · Proceedings of the 2nd Workshop on Human Evaluation of NLP Systems (HumEval)*
48. [Human evaluation of web-crawled parallel corpora for machine translation](https://aclanthology.org/2022.humeval-1.4/) *— 2022 · Proceedings of the 2nd Workshop on Human Evaluation of NLP Systems (HumEval)*
49. [Identifying Weaknesses in Machine Translation Metrics Through Minimum Bayes Risk Decoding: A Case Study for COMET](https://aclanthology.org/2022.aacl-main.83/) *— 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)*
50. [Improving Both Domain Robustness and Domain Adaptability in Machine Translation](https://aclanthology.org/2022.coling-1.461/) *— 2022 · Proceedings of the 29th International Conference on Computational Linguistics*
51. [Improving Jejueo-Korean Translation With Cross-Lingual Pretraining Using Japanese and Korean](https://aclanthology.org/2022.wat-1.3/) *— 2022 · Proceedings of the 9th Workshop on Asian Translation*
52. [Improving Specificity in Review Response Generation with Data-Driven Data Filtering](https://aclanthology.org/2022.ecnlp-1.15/) *— 2022 · Proceedings of the Fifth Workshop on e-Commerce and NLP (ECNLP 5)*
53. [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*
54. [Investigating Effectiveness of Multi-Encoder for Conversational Neural Machine Translation](https://aclanthology.org/2022.wmt-1.90/) *— 2022 · Proceedings of the Seventh Conference on Machine Translation (WMT)*
55. [Investigating Failures of Automatic Translation in the Case of Unambiguous Gender](https://aclanthology.org/2022.acl-long.243/) *— 2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
56. [Is NLP Ready for Standardization?](https://aclanthology.org/2022.findings-emnlp.202/) *— 2022 · Findings of the Association for Computational Linguistics: EMNLP 2022*
57. [Jojajovai: A Parallel Guarani-Spanish Corpus for MT Benchmarking](https://aclanthology.org/2022.lrec-1.226/) *— 2022 · Proceedings of the Thirteenth Language Resources and Evaluation Conference*
58. [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)*
59. [Local Structure Matters Most in Most Languages](https://aclanthology.org/2022.aacl-short.35/) *— 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 2: Short Papers)*
60. [Local Structure Matters Most: Perturbation Study in NLU](https://aclanthology.org/2022.findings-acl.293/) *— 2022 · Findings of the Association for Computational Linguistics: ACL 2022*
61. [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)*
62. [MTLens: Machine Translation Output Debugging](https://aclanthology.org/2022.lrec-1.448/) *— 2022 · Proceedings of the Thirteenth Language Resources and Evaluation Conference*
63. [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)*
64. [Machine Translation Between High-resource Languages in a Language Documentation Setting](https://aclanthology.org/2022.fieldmatters-1.3/) *— 2022 · Proceedings of the First Workshop on NLP applications to field linguistics*
65. [Models In a Spelling Bee: Language Models Implicitly Learn the Character Composition of Tokens](https://aclanthology.org/2022.naacl-main.373/) *— 2022 · Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies*
66. [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*
67. [Multilingual Machine Translation with Hyper-Adapters](https://aclanthology.org/2022.emnlp-main.77/) *— 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing*
68. [Multimodal Robustness for Neural Machine Translation](https://aclanthology.org/2022.emnlp-main.582/) *— 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing*
69. [NMTScore: A Multilingual Analysis of Translation-based Text Similarity Measures](https://aclanthology.org/2022.findings-emnlp.15/) *— 2022 · Findings of the Association for Computational Linguistics: EMNLP 2022*
70. [Non-Autoregressive Machine Translation: It”s Not as Fast as it Seems](https://aclanthology.org/2022.naacl-main.129/) *— 2022 · Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies*
71. [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*
72. [Of Human Criteria and Automatic Metrics: A Benchmark of the Evaluation of Story Generation](https://aclanthology.org/2022.coling-1.509/) *— 2022 · Proceedings of the 29th International Conference on Computational Linguistics*
73. [On the Interaction of Regularization Factors in Low-resource Neural Machine Translation](https://aclanthology.org/2022.eamt-1.14/) *— 2022 · Proceedings of the 23rd Annual Conference of the European Association for Machine Translation*
74. [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*
75. [Practical Attacks on Machine Translation using Paraphrase](https://aclanthology.org/2022.amta-research.17/) *— 2022 · Proceedings of the 15th biennial conference of the Association for Machine Translation in the Americas (Volume 1: Research Track)*
76. [Pre-Trained Multilingual Sequence-to-Sequence Models: A Hope for Low-Resource Language Translation?](https://aclanthology.org/2022.findings-acl.6/) *— 2022 · Findings of the Association for Computational Linguistics: ACL 2022*
77. [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*
78. [Proto-Gen: An end-to-end neural generator for persona and knowledge grounded response generation](https://aclanthology.org/2022.ccgpk-1.2/) *— 2022 · Proceedings of the 1st Workshop on Customized Chat Grounding Persona and Knowledge*
79. [Quality Estimation via Backtranslation at the WMT 2022 Quality Estimation Task](https://aclanthology.org/2022.wmt-1.54/) *— 2022 · Proceedings of the Seventh Conference on Machine Translation (WMT)*
80. [Quality-Aware Decoding for Neural Machine Translation](https://aclanthology.org/2022.naacl-main.100/) *— 2022 · Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies*
81. [Quantifying Synthesis and Fusion and their Impact on Machine Translation](https://aclanthology.org/2022.naacl-main.94/) *— 2022 · Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies*
82. [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/) *— our card · 2022 · Proceedings of the Seventh Conference on Machine Translation (WMT)*
83. [Revisiting Syllables in Language Modelling and Their Application on Low-Resource Machine Translation](https://aclanthology.org/2022.coling-1.374/) *— 2022 · Proceedings of the 29th International Conference on Computational Linguistics*
84. [Revisiting the Gold Standard: Grounding Summarization Evaluation with Robust Human Evaluation](https://arxiv.org/abs/2212.07981) *— 2022 · arXiv:2212.07981*
85. [Rewarding Semantic Similarity under Optimized Alignments for AMR-to-Text Generation](https://aclanthology.org/2022.acl-short.80/) *— 2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)*
86. [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)*
87. [Sampling-Based Approximations to Minimum Bayes Risk Decoding for Neural Machine Translation](https://aclanthology.org/2022.emnlp-main.754/) *— 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing*
88. [Samsung R&D Institute Poland Participation in WMT 2022](https://aclanthology.org/2022.wmt-1.17/) *— 2022 · Proceedings of the Seventh Conference on Machine Translation (WMT)*
89. [Searching for COMETINHO: The Little Metric That Could](https://aclanthology.org/2022.eamt-1.9/) *— 2022 · Proceedings of the 23rd Annual Conference of the European Association for Machine Translation*
90. [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)*
91. [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*
92. [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)*
93. [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*
94. [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*
95. [Test Set Sampling Affects System Rankings: Expanded Human Evaluation of WMT20 English-Inuktitut Systems](https://aclanthology.org/2022.wmt-1.8/) *— 2022 · Proceedings of the Seventh Conference on Machine Translation (WMT)*
96. [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)*
97. [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)*
98. [Transfer Learning and Masked Generation for Answer Verbalization](https://aclanthology.org/2022.suki-1.6/) *— 2022 · Proceedings of the Workshop on Structured and Unstructured Knowledge Integration (SUKI)*
99. [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*
100. [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)*

Pages: [1](https://md.research.elamur.ai/free/en/papers/popovic-2015-chrf-character-n-gram-f/cited-by/) · … · [8](https://md.research.elamur.ai/free/en/papers/popovic-2015-chrf-character-n-gram-f/cited-by/page/8/) · **9** · [10](https://md.research.elamur.ai/free/en/papers/popovic-2015-chrf-character-n-gram-f/cited-by/page/10/) · [11](https://md.research.elamur.ai/free/en/papers/popovic-2015-chrf-character-n-gram-f/cited-by/page/11/)