Meteor: an automatic metric for MT evaluation with high levels of correlation with human judgments

BLEU: a method for automatic evaluation of machine translation

Papineni, K., Roukos, S., Ward, T., & Zhu, W.-J. (2001) · Proceedings of the 40th Annual Meeting on Association for Computational Linguistics - ACL '02 · doi:10.3115/1073083.1073135 · Cited by 21,344

Untitled work

(2005) · Cited by 4,152

Minimum error rate training in statistical machine translation

Och, F. J. (2003) · Proceedings of the conference - Association for Computational Linguistics. Meeting · doi:10.3115/1075096.1075117 · Cited by 2,728

A Study of Translation Edit Rate with Targeted Human Annotation

Snover, M., Dorr, B. J., Schwartz, R. M., Micciulla, L., & Makhoul, J. I. (2006) · Cited by 2,380

Confidence estimation for machine translation

Blatz, J., Fitzgerald, E., Foster, G. F., Gandrabur, S., Goutte, C., Kulesza, A., Sanchís, A., & Ueffing, N. (2004) · International Conference on Computational Linguistics · doi:10.3115/1220355.1220401 · Cited by 368

Lattice-based minimum error rate training for statistical machine translation

Macherey, W., Och, F. J., Thayer, I., & Uszkoreit, J. (2008) · Conference on Empirical Methods in Natural Language Processing (EMNLP) · doi:10.3115/1613715.1613807 · Cited by 347

Precision and recall of machine translation

Melamed, I. D., Green, R., & Turian, J. P. (2003) · Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL-HLT) · doi:10.3115/1073483.1073504 · Cited by 228

The Significance of Recall in Automatic Metrics for MT Evaluation

Lavie, A., Sagae, K., & Jayaraman, S. (2004) · Lecture notes in computer science · doi:10.1007/978-3-540-30194-3_16 · Cited by 123

CDER: Efficient MT Evaluation Using Block Movements.

Leusch, G., Ueffing, N., & Ney, H. (2006) · RWTH Publications (RWTH Aachen) · Cited by 109

Information Retrieval

(2024) · ACM eBooks · doi:10.1145/3674127 · Cited by 86

On the Generation of Medical Dialogs for COVID-19

Zhou, M., Li, Z., Tan, B., Zeng, G., Yang, W., He, X., Ju, Z., Chakravorty, S., Chen, S., Yang, X., et al. (2021) · doi:10.18653/v1/2021.acl-short.112 · Cited by 16

Evaluation of Machine Translation Metrics for Czech as the Target Language

Kos, K., & Bojar, O. (2009) · The Prague Bulletin of Mathematical Linguistics · doi:10.2478/v10108-009-0026-2 · Cited by 15

Automatic improvement of machine translation systems

Llitjós, A. F. (2007) · Cited by 15

On the Generation of Medical Dialogues for COVID-19Preprint

Yang, W., Zeng, G., Tan, B., Ju, Z., Chakravorty, S., He, X., Chen, S., Yang, X., Wu, Q., Yu, Z., et al. (2020) · medRxiv · doi:10.1101/2020.05.08.20095810 · Cited by 15

Multi-task Regularization Based on Infrequent Classes for Audio CaptioningPreprint

Çakır, E., Drossos, K., & Virtanen, T. I. (2020) · arXiv (Cornell University) · doi:10.48550/arxiv.2007.04660 · Cited by 15

CL4AC: A Contrastive Loss for Audio CaptioningPreprint

Liu, X., Huang, Q., Mei, X., Ko, T., Tang, H. L., Plumbley, M. D., & Wang, W. (2021) · arXiv (Cornell University) · doi:10.48550/arxiv.2107.09990 · Cited by 15

USAAR-SAPE: An English–Spanish Statistical Automatic Post-Editing System

Pal, S., Vela, M., Naskar, S. K., & van Genabith, J. (2015) · Conference on Machine Translation (WMT) · doi:10.18653/v1/w15-3026 · Cited by 14

Multi-GRU Based Automated Image Captioning for Smartphones

KESKİN, R., MORAL, Ö. T., Kılıç, V., & Onan, A. (2021) · Signal Processing and Communications Applications Conference (SIU) · doi:10.1109/siu53274.2021.9477901 · Cited by 14

Graph Attention for Automated Audio Captioning

Xiao, F., Guan, J., Zhu, Q., & Wang, W. (2023) · IEEE Signal Processing Letters · doi:10.1109/lsp.2023.3266114 · Cited by 14

Is Relevance Propagated from Retriever to Generator in RAG?

Tian, F., Ganguly, D., & Macdonald, C. (2025) · Lecture notes in computer science · doi:10.1007/978-3-031-88708-6_3 · Cited by 14

A generalised alignment template formalism and its application to the inference of shallow-transfer machine translation rules from scarce bilingual corpora

Sánchez-Cartagena, V. M., Pérez-Ortiz, J. A., & Sánchez-Martínez, F. (2014) · Computer Speech & Language · doi:10.1016/j.csl.2014.10.003 · Cited by 14

Comparative Quality Estimation: Automatic Sentence-Level Ranking of Multiple Machine Translation Outputs

Avramidis, E. (2012) · Cited by 14

USAAR: An Operation Sequential Model for Automatic Statistical Post-Editing

Pal, S., Zampieri, M., & van Genabith, J. (2016) · Conference on Machine Translation (WMT) · doi:10.18653/v1/w16-2379 · Cited by 14

Stage-wise Fine-tuning for Graph-to-Text Generation

Wang, Q., Yavuz, S., Lin, X., Ji, H., & Rajani, N. F. (2021) · doi:10.18653/v1/2021.acl-srw.2 · Cited by 14

Contrastive Representation Learning for Exemplar-Guided Paraphrase Generation

Yang, H., Lam, W. P., & Li, P. (2021) · Findings of the Association for Computational Linguistics: EMNLP (Findings of EMNLP) · doi:10.18653/v1/2021.findings-emnlp.409 · Cited by 14

Linguistic Mathematical Relationships Saved or Lost in Translating Texts: Extension of the Statistical Theory of Translation and Its Application to the New Testament

Matricciani, E. (2022) · Information · doi:10.3390/info13010020 · Cited by 14

Layer-wise enhanced transformer with multi-modal fusion for image caption

Li, J., Wang, Y., & Zhao, D. (2022) · Multimedia Systems · doi:10.1007/s00530-022-01036-z · Cited by 14

Quality Estimation for Machine Translation Using the Joint Method of Evaluation Criteria and Statistical Modeling

Han, A. L.-F., Lü, Y., Wong, D. F., Chao, L. S., He, L., & Xing, J. (2013) · Cited by 14

Template-free Data-to-Text Generation of Finnish Sports NewsPreprint

Kanerva, J., Rönnqvist, S., Kekki, R., Salakoski, T., & Ginter, F. (2019) · arXiv (Cornell University) · doi:10.48550/arxiv.1910.01863 · Cited by 14

Assessing the role of AI in advancing construction sector industrial symbiosis research: a comparative study of leading digital assistants

Genç, O. (2024) · Environment Development and Sustainability · doi:10.1007/s10668-024-05794-w · Cited by 14

Can machine translation match human expertise? Quantifying the performance of large language models in the translation of patient-reported outcome measures (PROMs)

Lu, S.-C., Xu, C., Kaur, M. N., Edelen, M. O., Pusic, A. L., & Sidey-Gibbons, C. J. (2025) · Journal of Patient-Reported Outcomes · doi:10.1186/s41687-025-00926-w · Cited by 13

Automated Evaluation of the Virtual Assistant in Bleu and Rouge Scores

Chatoui, H., & Ata, O. (2021) · International Congress on Human-Computer Interaction, Optimization and Robotic Applications (ICHORA) · doi:10.1109/hora52670.2021.9461351 · Cited by 13

ArtCap: A Dataset for Image Captioning of Fine Art Paintings

Lu, Y., Guo, C., Dai, X., & Wang, F. (2022) · IEEE Transactions on Computational Social Systems · doi:10.1109/tcss.2022.3223539 · Cited by 14

AVI-Talking: Learning Audio-Visual Instructions for Expressive 3D Talking Face Generation

Sun, Y., Chu, W., Zhou, H., Wang, K., & Koike, H. (2024) · IEEE Access · doi:10.1109/access.2024.3390182 · Cited by 17

Question Answering for Electronic Health Records: Scoping Review of Datasets and Models

Bardhan, J., Roberts, K. E., & Wang, D. Z. (2024) · Journal of Medical Internet Research · doi:10.2196/53636 · Cited by 17

Automatic Job Safety Report Generation using RAG-based LLMs

Bernardi, M. L., Cimitile, M., & Pecori, R. (2024) · International Joint Conference on Neural Networks (IJCNN) · doi:10.1109/ijcnn60899.2024.10651320 · Cited by 13

MedDoc-Bot: A Chat Tool for Comparative Analysis of Large Language Models in the Context of the Pediatric Hypertension Guideline

Jabarulla, M. Y., Oeltze‐Jafra, S., Beerbaum, P., & Uden, T. (2024) · Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) · doi:10.1109/embc53108.2024.10781509 · Cited by 13

Sentence-level ranking with quality estimation

Avramidis, E. (2013) · Machine Translation · doi:10.1007/s10590-013-9144-6 · Cited by 13

BLEU Evaluation of Machine-Translated English-Croatian Legislation

Seljan, S., Brkić, M., & Vičić, T. (2012) · Language Resources and Evaluation Conference (LREC) · doi:10.63317/45d2z5emywy7 · Cited by 13

Syntactic Manipulation for Generating more Diverse and Interesting Texts

Deriu, J., & Cieliebak, M. (2018) · International Conference on Natural Language Generation · doi:10.18653/v1/w18-6503 · Cited by 13

Video Caption Based Searching Using End-to-End Dense Captioning and Sentence Embeddings

Aggarwal, A., Chauhan, A., Kumar, D., Mittal, M., Roy, S. S., & Kim, T.-H. (2020) · Symmetry · doi:10.3390/sym12060992 · Cited by 13

Spell Checking Techniques for Replacement of Unknown Words and Data Cleaning for Haitian Creole SMS Translation

Stymne, S. (2011) · Cited by 13

Generating Paraphrase with Topic as Prior Knowledge

Liu, Y., Lin, Z., Liu, F., Dai, Q., & Wang, W. (2019) · ACM International Conference on Information and Knowledge Management (CIKM) · doi:10.1145/3357384.3358102 · Cited by 13

Quality Assurance for Automated Commit Message Generation

Wang, B., Yan, M. L., Liu, Z., Xu, L., Xia, X., Zhang, X., & Yang, D. (2021) · IEEE International Conference on Software Analysis, Evolution and Reengineering (SANER) · doi:10.1109/saner50967.2021.00032 · Cited by 13

AggGen: Ordering and Aggregating while Generating

Xu, X., Dušek, O., Rieser, V., & Konstas, I. (2021) · doi:10.18653/v1/2021.acl-long.113 · Cited by 17

Evaluating English to Arabic machine translators

Hailat, T. M., Al-Kabi, M. N., Alsmadi, I. M., & Al-Shawakfa, E. M. (2013) · IEEE Jordan Conference on Applied Electrical Engineering and Computing Technologies · doi:10.1109/aeect.2013.6716439 · Cited by 13

Guiding Visual Question Generation

Vedd, N., Wang, Z., Rei, M., Miao, Y., & Specia, L. (2022) · Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies · doi:10.18653/v1/2022.naacl-main.118 · Cited by 12

Harnessing the Power of LLMs, Informers and Decision Transformers for Intent-Driven RAN Management in 6G

Habib, M. A., Iturria-Rivera, P. E., Ozcan, Y., Elsayed, M., Bavand, M., Gaigalas, R., & Erol‐Kantarci, M. (2025) · IEEE Transactions on Network Science and Engineering · doi:10.1109/tnse.2025.3596028 · Cited by 12

Performance Assessment of Large Language Models in Medical Consultation: Comparative Study

Seo, S., Kim, K., & Yang, H. (2025) · JMIR Medical Informatics · doi:10.2196/64318 · Cited by 12

Exploration of the optimal deep learning model for english-Japanese machine translation of medical device adverse event terminology

Yagahara, A., Uesugi, M., & Yokoi, H. (2025) · BMC Medical Informatics and Decision Making · doi:10.1186/s12911-025-02912-0 · Cited by 12

Cross-Modal Knowledge Diffusion-Based Generation for Difference-Aware Medical VQA

Lin, Q., He, K., Zhu, Y., Xu, F., Cambria, E., & Feng, M. (2025) · IEEE Transactions on Image Processing · doi:10.1109/tip.2025.3558446 · Cited by 17

How Propense Are Large Language Models at Producing Code Smells? A Benchmarking Study

Velasco, A., Rodríguez-Cárdenas, D., Alif, L. R., Palacio, D. N., & Poshyvanyk, D. (2025) · IEEE/ACM International Conference on Software Engineering: New Ideas and Emerging Results (ICSE-NIER) · doi:10.1109/icse-nier66352.2025.00025 · Cited by 12

Statistical Machine Translation

Specia, L. (2012) · IGI Global eBooks · doi:10.4018/978-1-4666-2169-5.ch004 · Cited by 12

Low-Resource Speech-to-Text Translation

Bansal, S., Kamper, H., Livescu, K., Lopez, A., & Goldwater, S. J. (2018) · Interspeech (USB) · doi:10.21437/interspeech.2018-1326 · Cited by 19

Designing a Symbolic Intermediate Representation for Neural Surface Realization

Elder, H., Foster, J., Barry, J., & O’Connor, A. (2019) · doi:10.18653/v1/w19-2308 · Cited by 12

TMRGM: A Template-Based Multi-Attention Model for X-Ray Imaging Report Generation

Wang, X., Zhang, Y., Guo, Z. H., & Li, J. (2021) · Journal of Artificial Intelligence for Medical Sciences · doi:10.2991/jaims.d.210428.002 · Cited by 12

Local Information Assisted Attention-Free Decoder for Audio Captioning

Xiao, F., Guan, J., Lan, H., Zhu, Q., & Wang, W. (2022) · IEEE Signal Processing Letters · doi:10.1109/lsp.2022.3189536 · Cited by 12

A Task-oriented Chatbot Based on LSTM and Reinforcement Learning

Hsueh, Y.-L., & Chou, T.-L. (2022) · ACM Transactions on Asian and Low-Resource Language Information Processing · doi:10.1145/3529649 · Cited by 12

Position-aware image captioning with spatial relation

Duan, Y., Wang, Z., Wang, J., Wang, Y., & Lin, C. (2022) · Neurocomputing · doi:10.1016/j.neucom.2022.05.003 · Cited by 13

StyleBabel: Artistic Style Tagging and Captioning

Ruta, D., Gilbert, A., Aggarwal, P., Marri, N., Kale, A., Briggs, J., Speed, C., Jin, H., Faieta, B., Filipkowski, A., et al. (2022) · Lecture notes in computer science · doi:10.1007/978-3-031-20074-8_13 · Cited by 12

Affective Image Captioning for Visual Artworks Using Emotion-Based Cross-Attention Mechanisms

Ishikawa, S., & Sugiura, K. (2023) · IEEE Access · doi:10.1109/access.2023.3255887 · Cited by 12

An Enhanced Method for Neural Machine Translation via Data Augmentation Based on the Self-Constructed English-Chinese Corpus, WCC-EC

Zhang, J., Guo, C., Mao, J., Guo, C., & Matsumoto, T. (2023) · IEEE Access · doi:10.1109/access.2023.3323756 · Cited by 12

Learning sign language machine translation based on elastic net regularization and latent semantic analysis

Boulares, M., & Jemni, M. (2016) · Artificial Intelligence Review · doi:10.1007/s10462-016-9460-3 · Cited by 12

A Learning-Exploring Method to Generate Diverse Paraphrases with Multi-Objective Deep Reinforcement Learning

Liu, M., Yang, E., Xiong, D., Zhang, Y., Meng, Y., Hu, C., Xu, J., & Chen, Y. (2020) · International Conference on Computational Linguistics · doi:10.18653/v1/2020.coling-main.209 · Cited by 12

Machine Translation Pre-training for Data-to-Text Generation - A Case Study in Czech

Kale, M., & Roy, S. (2020) · International Conference on Natural Language Generation · doi:10.18653/v1/2020.inlg-1.13 · Cited by 14

Cross-lingual Sentence Compression for Subtitles.

Aziz, W. F., de Sousa, S. C. M., & Specia, L. (2012) · Cited by 12

Connecting Phrase based Statistical Machine Translation AdaptationPreprint

Wang, R., Zhao, H., Lu, B., Utiyama, M., & Sumita, E. (2016) · arXiv (Cornell University) · doi:10.48550/arxiv.1607.08693 · Cited by 12

Measuring acceptability of machine translated enterprise content

Castilho, S. (2016) · Arrow@dit (Dublin Institute of Technology) · Cited by 12

A Survey of Document Grounded Dialogue Systems (DGDS)Preprint

Ma, L., Zhang, W., Li, M., & Liu, T. (2020) · arXiv (Cornell University) · doi:10.48550/arxiv.2004.13818 · Cited by 15

Zero-shot Fact Verification by Claim GenerationPreprint

Pan, L., Chen, W., Xiong, W., Kan, M., & Wang, W. Y. (2021) · arXiv (Cornell University) · doi:10.48550/arxiv.2105.14682 · Cited by 15

Contrastive Lexical Evaluation of Machine Translation

Max, A., Crego, J., & Yvon, F. (2010) · Language Resources and Evaluation Conference (LREC) · doi:10.63317/4e9cnp8tfbb3 · Cited by 11

Treatment of Markup in Statistical Machine Translation

Müller, M. (2017) · Workshop on Discourse in Machine Translation (DiscoMT) · doi:10.18653/v1/w17-4804 · Cited by 11

An automatic evaluation metric for Ancient-Modern Chinese translation

Yang, K., Liu, D., Qu, Q., Sang, Y., & Lv, J. (2020) · Neural Computing and Applications · doi:10.1007/s00521-020-05216-8 · Cited by 11

Using natural language generation to bootstrap missing Wikipedia articles: A human-centric perspective

Kaffee, L.-A., Vougiouklis, P., & Simperl, E. P. B. (2021) · Semantic Web · doi:10.3233/sw-210431 · Cited by 12

Dark-Side Avoidance of Mobile Applications With Data Biases Elimination in Socio-Cyber World

Ma, Y., Yu, C., Yan, M., Sangaiah, A. K., & Wu, Y. (2023) · IEEE Transactions on Computational Social Systems · doi:10.1109/tcss.2023.3264696 · Cited by 11

Linguistic Communication Channels Reveal Connections between Texts: The New Testament and Greek Literature

Matricciani, E. (2023) · Information · doi:10.3390/info14070405 · Cited by 11

Textual Explanations for Automated Commentary Driving

Kühn, M. A., Omeiza, D., & Kunze, L. (2023) · IEEE Intelligent Vehicles Symposium · doi:10.1109/iv55152.2023.10186611 · Cited by 11

Mobilenet V3-transformer, a lightweight model for image caption

Zhang, X., Fan, M., & Hou, M. (2024) · International Journal of Computers and Applications · doi:10.1080/1206212x.2024.2328498 · Cited by 11

Description of the Chinese-to-Spanish Rule-Based Machine Translation System Developed Using a Hybrid Combination of Human Annotation and Statistical Techniques

Costa‐jussà, M. R., & Centelles, J. (2015) · ACM Transactions on Asian and Low-Resource Language Information Processing · doi:10.1145/2738045 · Cited by 11

UdS-Sant: English–German Hybrid Machine Translation System

Pal, S., Naskar, S. K., & van Genabith, J. (2015) · Conference on Machine Translation (WMT) · doi:10.18653/v1/w15-3017 · Cited by 11

Orthographic and Morphological Processing for Persian-to-English Statistical Machine Translation

Rasooli, M. S., Kholy, A. E., & Habash, N. Y. (2013) · Cited by 11

Taking on new challenges in multi-word unit processing for machine translation

Monti, J., Barreiro, A. M., Elia, A., Marano, F., & Napoli, A. (2011) · RECERCAT (Consorci de Serveis Universitaris de Catalunya) · Cited by 11

Choosing the best machine translation system to translate a sentence by using only source-language information

Sánchez-Martínez, F. (2011) · RUA, Repositorio Institucional de la Universidad de Alicante (Universidad de Alicante) · Cited by 11

Large scale datasets for Image and Video Captioning in Italian

Scaiella, A., Croce, D., & Basili, R. (2019) · Italian Journal of Computational Linguistics · doi:10.4000/ijcol.478 · Cited by 11

Text Harmonization Strategies for Phrase-Based Statistical Machine Translation

Stymne, S. (2012) · Cited by 11

An improved statistical transfer system for French--English machine translation

Hanneman, G., Ambati, V., Clark, J. H., Parlikar, A., & Lavie, A. (2009) · Conference on Machine Translation (WMT) · doi:10.3115/1626431.1626460 · Cited by 11

Evaluating User Preferences in Machine Translation Using Conjoint Analysis

Kirchhoff, K., Daniel Capurro, N., & Turner, A. M. (2012) · Cited by 11

WaveTransformer: An Architecture for Audio Captioning Based on Learning Temporal and Time-Frequency Information

Tran, A., Drossos, K., & Virtanen, T. I. (2021) · European Signal Processing Conference (EUSIPCO) · doi:10.23919/eusipco54536.2021.9616340 · Cited by 11

Towards Generating Diverse Audio Captions via Adversarial Training

Mei, X., Liu, X., Sun, J., Plumbley, M. D., & Wang, W. (2024) · IEEE/ACM Transactions on Audio Speech and Language Processing · doi:10.1109/taslp.2024.3416686 · Cited by 12

Pragmatically Informative Text GenerationPreprint

Shen, S., Fried, D., Andreas, J., & Klein, D. (2019) · arXiv (Cornell University) · doi:10.48550/arxiv.1904.01301 · Cited by 11

Remote Sensing Image Change Captioning: A Comprehensive Review

Zou, S., Wei, Y., Xie, Y., Lao, M., & Luan, X. (2025) · International Journal of Multimedia Information Retrieval · doi:10.1007/s13735-025-00375-7 · Cited by 12

Automatic Generation of Job Safety Reports with Explainable RAG-Based LLMs

Bernardi, M. L., Cimitile, M., Panella, G., Pecori, R., & Simoncelli, G. (2025) · Information Systems Frontiers · doi:10.1007/s10796-025-10634-x · Cited by 10

Joint Underwater Image Enhancement and Captioning Through Multisupervised Chained Task Learning

Li, H., Li, L., Wang, H., Zhang, W., Liu, J., & Ren, P. (2026) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2026.3710783 · Cited by 10

An Entity-Focused Approach to Generating Company Descriptions

Saldanha, G., Biran, O., McKeown, K. R., & Gliozzo, A. (2016) · Proceedings of the conference - Association for Computational Linguistics. Meeting · doi:10.18653/v1/p16-2040 · Cited by 10

Augmenting Modelers with Semantic Autocompletion of Processes

Goldstein, M., & González-Álvarez, C. (2021) · Lecture notes in business information processing · doi:10.1007/978-3-030-85440-9_2 · Cited by 10

OSVidCap: A Framework for the Simultaneous Recognition and Description of Concurrent Actions in Videos in an Open-Set Scenario

Inácio, A. D. S., Gutoski, M., Lazzaretti, A. E., & Lopes, H. S. (2021) · IEEE Access · doi:10.1109/access.2021.3116882 · Cited by 10

Auxiliary Classifier based Residual RNN for Image Captioning

ÇAYLI, Ö., Kılıç, V., Onan, A., & Wang, W. (2022) · European Signal Processing Conference (EUSIPCO) · doi:10.23919/eusipco55093.2022.9909624 · Cited by 10

Comparison of Evaluation Metrics for Short Story Generation

Netisopakul, P., & Taoto, U. (2023) · IEEE Access · doi:10.1109/access.2023.3337095 · Cited by 10

Comparative Evaluation of Large Language Models for Abstractive Summarization

Bharathi Mohan, G., Kumar, R. P., Daniel., V. J., Archanaa., N., Faheem, M., T, S. K. J. D., & Kousihik., K. (2024) · International Conference on Cloud Computing, Data Science & Engineering (Confluence) · doi:10.1109/confluence60223.2024.10463521 · Cited by 11

Comparative evaluation and shared tasks for NLG in interactive systems

Belz, A., & Hastie, H. (2014) · Cambridge University Press eBooks · doi:10.1017/cbo9780511844492.013 · Cited by 10

An automatic evaluation of machine translation and Slavic languages

Munková, D., & Munk, M. (2014) · IEEE International Conference on Application of Information and Communication Technologies (AICT) · doi:10.1109/icaict.2014.7035992 · Cited by 10

Online Versus Offline NMT Quality: An In-depth Analysis on English-German and German-English

Elbayad, M., Ustaszewski, M., Esperança-Rodier, E., Brunet-Manquat, F., Verbeek, J. J., & Besacier, L. (2020) · International Conference on Computational Linguistics · doi:10.18653/v1/2020.coling-main.443 · Cited by 10

Evaluation of Machine Translation Methods applied to Medical Terminologies

Skianis, K., Briand, Y., & Desgrippes, F. (2020) · International Workshop on Health Text Mining and Information Analysis (LOUHI) · doi:10.18653/v1/2020.louhi-1.7 · Cited by 10

Gamayun - Language Technology for Humanitarian Response

Öktem, A., Jaam, M. A., DeLuca, E., & Tang, G. (2020) · IEEE Global Humanitarian Technology Conference (GHTC) · doi:10.1109/ghtc46280.2020.9342939 · Cited by 10

An Oblivious Approach to Machine Translation Quality Estimation

Elmakias, I., & Vilenchik, D. (2021) · Mathematics · doi:10.3390/math9172090 · Cited by 10

Improve Image Captioning by Estimating the Gazing Patterns from the Caption

Alahmadi, R., & Hahn, J. K. (2022) · IEEE Winter Conference on Applications of Computer Vision · doi:10.1109/wacv51458.2022.00251 · Cited by 11

Efficient Modeling of Future Context for Image Captioning

Fei, Z. (2022) · ACM International Conference on Multimedia (ACM MM) · doi:10.1145/3503161.3547840 · Cited by 11

Multi-Engine and Multi-Alignment Based Automatic Post-Editing and its Impact on Translation Productivity

Pal, S., Naskar, S. K., & van Genabith, J. (2016) · International Conference on Computational Linguistics · Cited by 10

Instance-based Deep Transfer Learning on Cross-domain Image Captioning

Perdana, R. S., & Ishida, Y. (2019) · International Electronics Symposium (IES) · doi:10.1109/elecsym.2019.8901660 · Cited by 10

Textual Entailment Using Different Similarity Metrics

Saikh, T., Naskar, S. K., Giri, C., & Bandyopadhyay, S. (2015) · Lecture notes in computer science · doi:10.1007/978-3-319-18111-0_37 · Cited by 10

METEOR: An Automatic Metric for MT Evaluation with Improved Correlation with Human Judgments

Lavie, A., & Agarwal, A. (2005)

The Meteor metric for automatic evaluation of machine translation

Lavie, A., & Denkowski, M. (2009) · Machine Translation · doi:10.1007/s10590-009-9059-4 · Cited by 351

Meteor 1.3: Automatic Metric for Reliable Optimization and Evaluation of Machine Translation Systems

Denkowski, M., & Lavie, A. (2011) · Cited by 344

Meteor, m-bleu and m-ter: Evaluation Metrics for High-Correlation with Human Rankings of Machine Translation Output

Agarwal, A., & Lavie, A. (2008)

METEOR, M-BLEU and M-TER

Agarwal, A., & Lavie, A. (2008) · Conference on Machine Translation (WMT) · doi:10.3115/1626394.1626406 · Cited by 109