---
title: "Who cites COMET: A Neural Framework for MT Evaluation"
description: "1,167 papers of the Elamur Research library cite «COMET: A Neural Framework for MT Evaluation», found in their bibliographies · page 1 of 2 · 1–100; the…"
canonical: "https://research.elamur.ai/free/en/papers/rei-2020-comet-neural-framework-mt-evaluation/cited-by/"
---
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# Who cites «COMET: A Neural Framework for MT Evaluation»

1,167 papers of our library cite it (of the 140,884 whose bibliographies we read) · 117 with a page here, the most cited first · page 1 of 2 · 1–100 · [← the paper](https://md.research.elamur.ai/free/en/papers/rei-2020-comet-neural-framework-mt-evaluation/)

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1. [**BARTScore: Evaluating Generated Text as Text Generation**Weizhe Yuan, Graham Neubig, Pengfei Liu*2021 · 806 citations*](https://md.research.elamur.ai/free/en/papers/yuan-2021-bartscore-evaluating-generated-text-text/)
2. [**Experts, Errors, and Context: A Large-Scale Study of Human Evaluation for Machine Translation**Markus Freitag, George Foster, David Grangier, et al.*2021 · 660 citations*](https://md.research.elamur.ai/free/en/papers/freitag-2021-experts-errors-context-large-scale/)
3. [**Multilingual Machine Translation with Large Language Models: Empirical Results and Analysis**Wenhao Zhu, Hongyi Liu, Qingxiu Dong, et al.*2024 · 503 citations*](https://md.research.elamur.ai/free/en/papers/zhu-2024-multilingual-machine-translation-large-language/)
4. [**COMET-22: Unbabel-IST 2022 Submission for the Metrics Shared Task**Ricardo Rei, José G. C. de Souza, Duarte Alves, et al.*2022 · 433 citations*](https://md.research.elamur.ai/free/en/papers/rei-2022-comet-22-unbabel-ist-2022/)
5. [**CometKiwi: IST-Unbabel 2022 Submission for the Quality Estimation Shared Task**Ricardo Rei, Marcos Treviso, Nuno M. Guerreiro, et al.*2022 · 325 citations*](https://md.research.elamur.ai/free/en/papers/rei-2022-cometkiwi-ist-unbabel-2022-submission/)
6. [**Document-Level Machine Translation with Large Language Models**Longyue Wang, Chenyang Lyu, Tianbo Ji, et al.*2023 · 295 citations*](https://md.research.elamur.ai/free/en/papers/wang-2023-document-level-machine-translation-large/)
7. [**Prompting Large Language Model for Machine Translation: A Case Study**Biao Zhang, Barry Haddow, Alexandra Birch*2023 · 293 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2023-prompting-large-language-model-machine/)
8. [**Is ChatGPT a Good NLG Evaluator? A Preliminary Study**Jiaan Wang, Yunlong Liang, Fandong Meng, et al.*2023 · 281 citations*](https://md.research.elamur.ai/free/en/papers/wang-2023-chatgpt-good-nlg-evaluator-preliminary/)
9. [**Results of WMT22 Metrics Shared Task: Stop Using BLEU – Neural Metrics Are Better and More Robust**Markus Freitag, Ricardo Rei, Nitika Mathur, et al.*2022 · 263 citations*](https://md.research.elamur.ai/free/en/papers/freitag-2022-results-wmt22-metrics-shared-task/)
10. [**In-context Examples Selection for Machine Translation**Sweta Agrawal, Chunting Zhou, Mike Lewis, et al.*2023 · 241 citations*](https://md.research.elamur.ai/free/en/papers/agrawal-2023-context-examples-selection-machine-translation/)
11. [**Reinforced Self-Training (ReST) for Language Modeling**Caglar Gulcehre, Tom Le Paine, Srivatsan Srinivasan, et al.*2023 · 209 citations*](https://md.research.elamur.ai/free/en/papers/gulcehre-2023-reinforced-self-training-rest-language/)
12. [**IndicTrans2: Towards High-Quality and Accessible Machine Translation Models for all 22 Scheduled Indian Languages**Jay Gala, Pranjal A. Chitale, Raghavan AK, et al.*2023 · 200 citations*](https://md.research.elamur.ai/free/en/papers/gala-2023-indictrans2-towards-high-quality-accessible/)
13. [**Results of the WMT20 Metrics Shared Task**Nitika Mathur, Johnny Wei, Markus Freitag, et al.*2020 · 195 citations*](https://md.research.elamur.ai/free/en/papers/mathur-2020-results-wmt20-metrics-shared-task/)
14. [**GEMBA-MQM: Detecting Translation Quality Error Spans with GPT-4**Tom Kocmi, Christian Federmann*2023 · 191 citations*](https://md.research.elamur.ai/free/en/papers/kocmi-2023-gemba-mqm-detecting-translation-quality/)
15. [**Towards Making the Most of ChatGPT for Machine Translation**Keqin Peng, Liang Ding, Qihuang Zhong, et al.*2023 · 190 citations*](https://md.research.elamur.ai/free/en/papers/peng-2023-making-most-chatgpt-machine-translation/)
16. [**Findings of the IWSLT 2022 Evaluation Campaign**Antonios Anastasopoulos, Loïc Barrault, Luisa Bentivogli, et al.*2022 · 177 citations*](https://md.research.elamur.ai/free/en/papers/anastasopoulos-2022-findings-iwslt-2022-evaluation-campaign/)
17. [**Results of the WMT21 Metrics Shared Task: Evaluating Metrics with Expert-based Human Evaluations on TED and News Domain**Markus Freitag, Ricardo Rei, Nitika Mathur, et al.*2021 · 169 citations*](https://md.research.elamur.ai/free/en/papers/freitag-2021-results-wmt21-metrics-shared-task/)
18. [**Results of WMT23 Metrics Shared Task: Metrics Might Be Guilty but References Are Not Innocent**Markus Freitag, Nitika Mathur, Chi-kiu Lo, et al.*2023 · 155 citations*](https://md.research.elamur.ai/free/en/papers/freitag-2023-results-wmt23-metrics-shared-task/)
19. [**FINDINGS OF THE IWSLT 2023 EVALUATION CAMPAIGN**Milind Agarwal, Sweta Agrawal, Antonios Anastasopoulos, et al.*2023 · 153 citations*](https://md.research.elamur.ai/free/en/papers/agarwal-2023-findings-iwslt-2023-evaluation-campaign/)
20. [**ChatGPT MT: Competitive for High- (but Not Low-) Resource Languages**Nathaniel Robinson, Perez Ogayo, David R. Mortensen, et al.*2023 · 151 citations*](https://md.research.elamur.ai/free/en/papers/robinson-2023-chatgpt-mt-competitive-high-but/)
21. [**Looking for a Needle in a Haystack: A Comprehensive Study of Hallucinations in Neural Machine Translation**Nuno M. Guerreiro, Elena Voita, André Martins*2023 · 147 citations*](https://md.research.elamur.ai/free/en/papers/guerreiro-2023-looking-needle-haystack-comprehensive-study/)
22. [**Quality-Aware Decoding for Neural Machine Translation**Patrick Fernandes, António Farinhas, Ricardo Rei, et al.*2022 · 143 citations*](https://md.research.elamur.ai/free/en/papers/fernandes-2022-quality-aware-decoding-neural-machine/)
23. [**Attributed Question Answering: Evaluation and Modeling for Attributed Large Language Models**Bernd Bohnet, Vinh Q. Tran, Pat Verga, et al.*2022 · 136 citations*](https://md.research.elamur.ai/free/en/papers/bohnet-2022-attributed-question-answering-evaluation-modeling/)
24. [**Error Analysis Prompting Enables Human-Like Translation Evaluation in Large Language Models**Qingyu Lu, Baopu Qiu, Liang Ding, et al.*2024 · 135 citations*](https://md.research.elamur.ai/free/en/papers/lu-2024-error-analysis-prompting-enables-human/)
25. [**Learning Compact Metrics for MT**Amy Pu, Hyung Won Chung, Ankur Parikh, et al.*2021 · 130 citations*](https://md.research.elamur.ai/free/en/papers/pu-2021-learning-compact-metrics-mt/)
26. [**Fanar: An Arabic-Centric Multimodal Generative AI Platform**Fanar Team: Ummar Abbas, Mohammad Shahmeer Ahmad, Firoj Alam, et al.*2025 · 127 citations*](https://md.research.elamur.ai/free/en/papers/abbas-2025-fanar-arabic-centric-multimodal-generative/)
27. [**INSTRUCTSCORE: Towards Explainable Text Generation Evaluation with Automatic Feedback**Wenda Xu, Danqing Wang, Liangming Pan, et al.*2023 · 122 citations*](https://md.research.elamur.ai/free/en/papers/xu-2023-instructscore-explainable-text-generation-evaluation/)
28. [**MetricX-24: The Google Submission to the WMT 2024 Metrics Shared Task**Juraj Juraska, Daniel Deutsch, Mara Finkelstein, et al.*2024 · 118 citations*](https://md.research.elamur.ai/free/en/papers/juraska-2024-metricx-24-google-submission-wmt/)
29. [**MetricX-23: The Google Submission to the WMT 2023 Metrics Shared Task**Juraj Juraska, Mara Finkelstein, Daniel Deutsch, et al.*2023 · 118 citations*](https://md.research.elamur.ai/free/en/papers/juraska-2023-metricx-23-google-submission-wmt/)
30. [**Benchmarking Machine Translation with Cultural Awareness**Binwei Yao, Ming Jiang, Tara Bobinac, et al.*2023 · 109 citations*](https://md.research.elamur.ai/free/en/papers/yao-2023-benchmarking-machine-translation-cultural-awareness/)
31. [**NTREX-128 – News Test References for MT Evaluation of 128 Languages**Christian Federmann, Tom Kocmi, Ying Xin*2022 · 104 citations*](https://md.research.elamur.ai/free/en/papers/federmann-2022-ntrex-128-news-test-references/)
32. [**LENS: A Learnable Evaluation Metric for Text Simplification**Mounica Maddela, Yao Dou, David Heineman, et al.*2023 · 103 citations*](https://md.research.elamur.ai/free/en/papers/maddela-2023-lens-learnable-evaluation-metric-text/)
33. [**UniTE: Unified Translation Evaluation**Yu Wan, Dayiheng Liu, Baosong Yang, et al.*2022 · 100 citations*](https://md.research.elamur.ai/free/en/papers/wan-2022-unite-unified-translation-evaluation/)
34. [**Unbabel's Participation in the WMT20 Metrics Shared Task**Ricardo Rei, Craig Stewart, Ana C Farinha, et al.*2020 · 98 citations*](https://md.research.elamur.ai/free/en/papers/rei-2020-unbabel-s-participation-wmt20-metrics/)
35. [**Findings of the WMT 2022 Shared Task on Quality Estimation**Chrysoula Zerva, Frédéric Blain, Ricardo Rei, et al.*2022 · 91 citations*](https://md.research.elamur.ai/free/en/papers/zerva-2022-findings-wmt-2022-shared-task/)
36. [**Are References Really Needed? Unbabel-IST 2021 Submission for the Metrics Shared Task**Ricardo Rei, Ana C Farinha, Chrysoula Zerva, et al.*2021 · 85 citations*](https://md.research.elamur.ai/free/en/papers/rei-2021-are-references-really-needed-unbabel/)
37. [**Bridging the Gap: A Survey on Integrating (Human) Feedback for Natural Language Generation**Patrick Fernandes, Aman Madaan, Emmy Liu, et al.*2023 · 84 citations*](https://md.research.elamur.ai/free/en/papers/fernandes-2023-bridging-gap-survey-integrating-human/)
38. [**Chain-of-Dictionary Prompting Elicits Translation in Large Language Models**Hongyuan Lu, Haoran Yang, Haoyang Huang, et al.*2024 · 81 citations*](https://md.research.elamur.ai/free/en/papers/lu-2024-chain-dictionary-prompting-elicits-translation/)
39. [**Iterative Translation Refinement with Large Language Models**Pinzhen Chen, Zhicheng Guo, Barry Haddow, et al.*2024 · 73 citations*](https://md.research.elamur.ai/free/en/papers/chen-2024-iterative-translation-refinement-large-language/)
40. [**Embarrassingly Easy Document-Level MT Metrics: How to Convert Any Pretrained Metric into a Document-Level Metric**Giorgos Vernikos, Brian Thompson, Prashant Mathur, et al.*2022 · 68 citations*](https://md.research.elamur.ai/free/en/papers/vernikos-2022-embarrassingly-easy-document-level-mt/)
41. [**A Fine-Grained Analysis of BERTScore**Michael Hanna, Ondřej Bojar*2021 · 62 citations*](https://md.research.elamur.ai/free/en/papers/hanna-2021-fine-grained-analysis-bertscore/)
42. [**TARJAMAT: Evaluation of Bard and ChatGPT on Machine Translation of Ten Arabic Varieties**Karima Kadaoui, Samar M. Magdy, Abdul Waheed, et al.*2023 · 60 citations*](https://md.research.elamur.ai/free/en/papers/kadaoui-2023-tarjamat-evaluation-bard-chatgpt-machine/)
43. [**Learning to Evaluate Translation Beyond English: BLEURT Submissions to the WMT Metrics 2020 Shared Task**Thibault Sellam, Amy Pu, Hyung Won Chung, et al.*2020 · 55 citations*](https://md.research.elamur.ai/free/en/papers/sellam-2020-learning-evaluate-translation-beyond-english/)
44. [**DiscoScore: Evaluating Text Generation with BERT and Discourse Coherence**Wei Zhao, Michael Strube, Steffen Eger*2023 · 53 citations*](https://md.research.elamur.ai/free/en/papers/zhao-2023-discoscore-evaluating-text-generation-bert/)
45. [**Fine-Tuned Machine Translation Metrics Struggle in Unseen Domains**Vilém Zouhar, Shuoyang Ding, Anna Currey, et al.*2024 · 32 citations*](https://md.research.elamur.ai/free/en/papers/zouhar-2024-fine-tuned-machine-translation-metrics/)
46. [**MaTESe: Machine Translation Evaluation as a Sequence Tagging Problem**Stefano Perrella, Lorenzo Proietti, Alessandro Scirè, et al.*2022 · 32 citations*](https://md.research.elamur.ai/free/en/papers/perrella-2022-matese-machine-translation-evaluation-as/)
47. [**ACES: Translation Accuracy Challenge Sets for Evaluating Machine Translation Metrics**Chantal Amrhein, Nikita Moghe, Liane Guillou*2022 · 29 citations*](https://md.research.elamur.ai/free/en/papers/amrhein-2022-aces-translation-accuracy-challenge-sets/)
48. [**Machine Translation Meta Evaluation through Translation Accuracy Challenge Sets**Nikita Moghe, Arnisa Fazla, Chantal Amrhein, et al.*2025 · 28 citations*](https://md.research.elamur.ai/free/en/papers/moghe-2025-machine-translation-meta-evaluation-through/)
49. [**M-MAD: Multidimensional Multi-Agent Debate for Advanced Machine Translation Evaluation**Zhaopeng Feng, Jiayuan Su, Jiamei Zheng, et al.*2025 · 24 citations*](https://md.research.elamur.ai/free/en/papers/feng-2025-m-mad-multidimensional-multi-agent/)
50. [**Guardians of the Machine Translation Meta-Evaluation: Sentinel Metrics Fall In!**Stefano Perrella, Lorenzo Proietti, Alessandro Scirè, et al.*2024 · 24 citations*](https://md.research.elamur.ai/free/en/papers/perrella-2024-guardians-machine-translation-meta-evaluation/)
51. [**GuoFeng: A Benchmark for Zero Pronoun Recovery and Translation**Mingzhou Xu, Longyue Wang, Derek F. Wong, et al.*2022 · 18 citations*](https://md.research.elamur.ai/free/en/papers/xu-2022-guofeng-benchmark-zero-pronoun-recovery/)
52. [**Lost in Translationese? Reducing Translation Effect Using Abstract Meaning Representation**Shira Wein, Nathan Schneider*2024 · 16 citations*](https://md.research.elamur.ai/free/en/papers/wein-2024-lost-translationese-reducing-translation-effect/)
53. [**Beyond Correlation: Interpretable Evaluation of Machine Translation Metrics**Stefano Perrella, Lorenzo Proietti, Pere-Lluís Huguet Cabot, et al.*2024 · 15 citations*](https://md.research.elamur.ai/free/en/papers/perrella-2024-beyond-correlation-interpretable-evaluation-machine/)
54. [**TigerCoder: A Novel Suite of LLMs for Code Generation in Bangla**Nishat Raihan, Antonios Anastasopoulos, Marcos Zampieri*2026 · 13 citations*](https://md.research.elamur.ai/free/en/papers/raihan-2026-tigercoder-novel-suite-llms-code/)
55. [**SSA-COMET: Do LLMs Outperform Learned Metrics in Evaluating MT for Under-Resourced African Languages?**Senyu Li, Jiayi Wang, Felermino D. M. A. Ali, et al.*2025 · 13 citations*](https://md.research.elamur.ai/free/en/papers/li-2025-ssa-comet-do-llms-outperform/)
56. [**TriFine: A Large-Scale Dataset of Vision-Audio-Subtitle for Tri-Modal Machine Translation and Benchmark with Fine-Grained Annotated Tags**Boyu Guan, Yining Zhang, Yang Zhao, et al.*2025 · 9 citations*](https://md.research.elamur.ai/free/en/papers/guan-2025-trifine-large-scale-dataset-vision/)
57. [**Advancing Dialectal Arabic to Modern Standard Arabic Machine Translation**Abdullah Alabdullah, Lifeng Han, Chenghua Lin*2025 · 8 citations*](https://md.research.elamur.ai/free/en/papers/alabdullah-2025-advancing-dialectal-arabic-modern-standard/)
58. [**Assessing the Role of Context in Chat Translation Evaluation: Is Context Helpful and Under What Conditions?**Sweta Agrawal, Amin Farajian, Patrick Fernandes, et al.*2024 · 8 citations*](https://md.research.elamur.ai/free/en/papers/agrawal-2024-assessing-role-context-chat-translation/)
59. [**Early-Exit and Instant Confidence Translation Quality Estimation**Vilém Zouhar, Maike Züfle, Beni Egressy, et al.*2026 · 6 citations*](https://md.research.elamur.ai/free/en/papers/zouhar-2026-early-exit-instant-confidence-translation/)
60. [**Beyond Literal Mapping: Benchmarking and Improving Non-Literal Translation Evaluation**Yanzhi Tian, Cunxiang Wang, Zeming Liu, et al.*2026 · 5 citations*](https://md.research.elamur.ai/free/en/papers/tian-2026-beyond-literal-mapping-benchmarking-improving/)
61. [**MoVoC: Morphology-Aware Subword Construction for Ge'ez Script Languages**Hailay Kidu Teklehaymanot, Dren Fazlija, Wolfgang Nejdl*2025 · 4 citations*](https://md.research.elamur.ai/free/en/papers/teklehaymanot-2025-movoc-morphology-aware-subword-construction/)
62. [**MoVoC: Morphology-Aware Subword Construction for Geez Script Languages**Hailay Kidu Teklehaymanot, Dren Fazlija, Wolfgang Nejdl*2025 · 4 citations*](https://md.research.elamur.ai/free/en/papers/teklehaymanot-2025-movoc-morphology-aware-subword-construction-geez/)
63. [**Domain Adaptation for Arabic Machine Translation: The Case of Financial Texts**Emad A. Alghamdi, Jezia Zakraoui, Fares A. Abanmy*2023 · 3 citations*](https://md.research.elamur.ai/free/en/papers/alghamdi-2023-domain-adaptation-arabic-machine-translation/)
64. [**Ara-HOPE: Human-Centric Post-Editing Evaluation for Dialectal Arabic to Modern Standard Arabic Translation**Abdullah Alabdullah, Lifeng Han, Chenghua Lin*2026 · 2 citations*](https://md.research.elamur.ai/free/en/papers/alabdullah-2026-ara-hope-human-centric-post/)
65. [**Bridging Scientific Heritage: An Arabic — Russian Parallel Corpus and LLM Benchmark for Sustainable Knowledge Transfer**Mullosharaf K. Arabov*2026 · 2 citations*](https://md.research.elamur.ai/free/en/papers/arabov-2026-bridging-scientific-heritage-arabic-russian/)
66. [**Remedy-R: Generative Reasoning for Machine Translation Evaluation without Error Annotations**Shaomu Tan, Ryosuke Mitani, Ritvik Choudhary, et al.*2026 · 2 citations*](https://md.research.elamur.ai/free/en/papers/tan-2026-remedy-r-generative-reasoning-machine/)
67. [**Who Watches the Watchmen? Humans Disagree With Translation Metrics on Unseen Domains**Finn Schmidt, Jan Philip Wahle, Terry Ruas, et al.*2026 · 2 citations*](https://md.research.elamur.ai/free/en/papers/schmidt-2026-who-watches-watchmen-humans-disagree/)
68. [**Biases in Translation: Assessing Opinion Distortion in Machine Translated Texts**Nazanin Shafiabadi, François Yvon*2026 · 1 citation*](https://md.research.elamur.ai/free/en/papers/shafiabadi-2026-biases-translation-assessing-opinion-distortion/)
69. [**Can LLMs Translate Italy's Language Varieties?**Edoardo Signoroni, Pavel Rychlý*2026 · 1 citation*](https://md.research.elamur.ai/free/en/papers/signoroni-2026-can-llms-translate-italy-s/)
70. [**Hurdles of Automatic Metric for Speech Translation Evaluation**Victor Eugen Zarzu, Vilem Zouhar*2026 · 1 citation*](https://md.research.elamur.ai/free/en/papers/zarzu-2026-hurdles-automatic-metric-speech-translation/)
71. [**IIIT-BGP IWSLT 2026 Systems for Low-resource ST**Kaustuk Pratap Singh, Dipanshu, Vedant Singh, et al.*2026 · 1 citation*](https://md.research.elamur.ai/free/en/papers/singh-2026-iiit-bgp-iwslt-2026-systems/)
72. [**Multilingual Communication in the Asylum Context: Evaluating LLM-Based Machine Translation with Fuzzy Match Augmentation and Adaptive NMT across Resource Conditions under Low-Data Constraints**Thomas Moerman, Arda Tezcan, Lieve Macken*2026 · 1 citation*](https://md.research.elamur.ai/free/en/papers/moerman-2026-multilingual-communication-asylum-context-evaluating/)
73. [**PEAR: Pairwise Evaluation for Automatic Relative Scoring in Machine Translation**Lorenzo Proietti, Roman Grundkiewicz, Matt Post*2026 · 1 citation*](https://md.research.elamur.ai/free/en/papers/proietti-2026-pear-pairwise-evaluation-automatic-relative/)
74. [**Recovered in Translation: Efficient Pipeline for Automated Translation of Benchmarks and Datasets**Hanna Yukhymenko, Anton Alexandrov, Martin Vechev*2026 · 1 citation*](https://md.research.elamur.ai/free/en/papers/yukhymenko-2026-recovered-translation-efficient-pipeline-automated/)
75. [**Revisiting Metric Reliability for Fine-grained Evaluation of Machine Translation and Summarization in Indian Languages**Amir Hossein Yari, Kalmit Kulkarni, Ahmad Raza Khan, et al.*2026 · 1 citation*](https://md.research.elamur.ai/free/en/papers/yari-2026-revisiting-metric-reliability-fine-grained/)
76. [**XQ-MEval: A Dataset with Cross-lingual Parallel Quality for Benchmarking Translation Metrics**Jingxuan Liu, Zhi Qu, Jin Tei, et al.*2026 · 1 citation*](https://md.research.elamur.ai/free/en/papers/liu-2026-xq-meval-dataset-cross-lingual/)
77. [**Adaptive Originality Filtering: Rejection Based Prompting and RiddleScore for Culturally Grounded Multilingual Riddle Generation**Duy Le, Kent Ziti, Evan Girard-Sun, et al.*2025 · 1 citation*](https://md.research.elamur.ai/free/en/papers/le-2025-adaptive-originality-filtering-rejection-based/)
78. [**Exploiting Task Reversibility of DRS Parsing and Generation: Challenges and Insights from a Multi-lingual Perspective**Muhammad Saad Amin, Luca Anselma, Alessandro Mazzei*2025 · 1 citation*](https://md.research.elamur.ai/free/en/papers/amin-2025-exploiting-task-reversibility-drs-parsing/)
79. [**Tokenisation in Machine Translation Does Matter: The impact of different tokenisation approaches for Maltese**Kurt Abela, Kurt Micallef, Marc Tanti, et al.*2024 · 1 citation*](https://md.research.elamur.ai/free/en/papers/abela-2024-tokenisation-machine-translation-does-matter/)
80. [**A Practical Evaluation Method for Long-Form Simultaneous Speech-to-Speech Translation**Yulin Xue, Siqi Ouyang, Lei Li*2026*](https://md.research.elamur.ai/free/en/papers/xue-2026-practical-evaluation-method-long-form/)
81. [**Ancient Greek to Modern Greek Machine Translation: A Novel Benchmark and Fine-Tuning Experiments on LLMs and NMT Models**Spyridon Mavromatis, Sokratis Sofianopoulos, Prokopis Prokopidis, et al.*2026*](https://md.research.elamur.ai/free/en/papers/mavromatis-2026-ancient-greek-modern-greek-machine/)
82. [**Assessing and Improving Punctuation Robustness in English-Marathi Machine Translation**Kaustubh Shivshankar Shejole, Sourabh Deoghare, Pushpak Bhattacharyya*2026*](https://md.research.elamur.ai/free/en/papers/shejole-2026-assessing-improving-punctuation-robustness-english/)
83. [**Benchmarking Arabic — Russian Machine Translation: A Comparison of Fine-tuned NMT and Few-shot LLMs under Rich Morphology and Low Lexical Overlap**Mullosharaf K. Arabov*2026*](https://md.research.elamur.ai/free/en/papers/arabov-2026-benchmarking-arabic-russian-machine-translation/)
84. [**Benchmarking Large Language Models for Game Localization Quality Assurance: A Cross-Model, Cross-Lingual Analysis**Mao Tian, Na Wu*2026*](https://md.research.elamur.ai/free/en/papers/tian-2026-benchmarking-large-language-models-game/)
85. [**Beyond Simple Term Injection: Reasoning Models for Legal Translation in a Non-Dominant Language Variety**Paolo Di Natale, Elena Chiocchetti, Marlies Alber, et al.*2026*](https://md.research.elamur.ai/free/en/papers/natale-2026-beyond-simple-term-injection-reasoning/)
86. [**Context-8: A Data Set for Evaluating Context Sensitivity in Machine Translation**Dongyue Wang, Kyo Kageura*2026*](https://md.research.elamur.ai/free/en/papers/wang-2026-context-8-data-set-evaluating/)
87. [**Cultural and Knowledge Biases in LLMs through the Lens of Entity-Aware Machine Translation**Lu Xu, Luca Moroni, Roberto Navigli*2026*](https://md.research.elamur.ai/free/en/papers/xu-2026-cultural-knowledge-biases-llms-through/)
88. [**Degree Zero of Translation: Using Interlinear Baselines to Quantify Translator Intervention**Maciej Rapacz, Aleksander Smywiński-Pohl*2026*](https://md.research.elamur.ai/free/en/papers/rapacz-2026-degree-zero-translation-interlinear-baselines/)
89. [**Diagnose, Then Repair: A Two-Stage MQM-Guided Post-Editing Framework for Domain-Specific Machine Translation**Ji Hun Wang, Siyu Wu*2026*](https://md.research.elamur.ai/free/en/papers/wang-2026-diagnose-then-repair-two-stage/)
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