---
title: "Who cites Nuno M. Guerreiro"
description: "920 papers of the Elamur Research library cite the works of Nuno M. Guerreiro, found in their bibliographies · page 1 of 2 · 1–100; the most cited first."
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---
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# Who cites Nuno M. Guerreiro

1,356 citations of their works from 920 papers of our library (of the 140,884 whose bibliographies we read) · 106 with a page here, the most cited first · page 1 of 2 · 1–100 · [← Nuno M. Guerreiro](https://md.research.elamur.ai/free/en/authors/nuno-m-guerreiro/)

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1. [**A Survey on Hallucination in Large Language Models: Principles, Taxonomy, Challenges, and Open Questions**Lei Huang, Weijiang Yu, Weitao Ma, et al.*2023 · 3,221 citations*](https://md.research.elamur.ai/free/en/papers/huang-2023-survey-hallucination-large-language-models/)
2. [**Siren's Song in the AI Ocean: A Survey on Hallucination in Large Language Models**Yue Zhang, Yafu Li, Leyang Cui, et al.*2023 · 962 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2023-siren-s-song-ai-ocean/)
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. [**xCOMET: Transparent Machine Translation Evaluation through Fine-grained Error Detection**Nuno M. Guerreiro, Ricardo Rei, Daan van Stigt, et al.*2024 · 333 citations*](https://md.research.elamur.ai/free/en/papers/guerreiro-2024-xcomet-transparent-machine-translation-evaluation/)
6. [**Hallucination is Inevitable: An Innate Limitation of Large Language Models**Ziwei Xu, Sanjay Jain, Mohan Kankanhalli*2024 · 309 citations*](https://md.research.elamur.ai/free/en/papers/xu-2024-hallucination-inevitable-innate-limitation-large/)
7. [**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/)
8. [**MedAgents: Large Language Models as Collaborators for Zero-shot Medical Reasoning**Xiangru Tang, Anni Zou, Zhuosheng Zhang, et al.*2024 · 244 citations*](https://md.research.elamur.ai/free/en/papers/tang-2024-medagents-large-language-models-as/)
9. [**Tower: An Open Multilingual Large Language Model for Translation-Related Tasks**Duarte M. Alves, Jose Pombal, Nuno M. Guerreiro, et al.*2024 · 226 citations*](https://md.research.elamur.ai/free/en/papers/alves-2024-tower-open-multilingual-large-language/)
10. [**Contrastive Preference Optimization: Pushing the Boundaries of LLM Performance in Machine Translation**Haoran Xu, Amr Sharaf, Yunmo Chen, et al.*2024 · 207 citations*](https://md.research.elamur.ai/free/en/papers/xu-2024-contrastive-preference-optimization-pushing-boundaries/)
11. [**Exploring Human-Like Translation Strategy with Large Language Models**Zhiwei He, Tian Liang, Wenxiang Jiao, et al.*2024 · 207 citations*](https://md.research.elamur.ai/free/en/papers/he-2024-exploring-human-like-translation-strategy/)
12. [**Aya Expanse: Combining Research Breakthroughs for a New Multilingual Frontier**John Dang, Shivalika Singh, Daniel D'souza, et al.*2024 · 180 citations*](https://md.research.elamur.ai/free/en/papers/dang-2024-aya-expanse-combining-research-breakthroughs/)
13. [**Findings of the WMT24 General Machine Translation Shared Task: The LLM Era Is Here but MT Is Not Solved Yet**Tom Kocmi, Eleftherios Avramidis, Rachel Bawden, et al.*2024 · 177 citations*](https://md.research.elamur.ai/free/en/papers/kocmi-2024-findings-wmt24-general-machine-translation/)
14. [**Large Language Models Effectively Leverage Document-level Context for Literary Translation, but Critical Errors Persist**Marzena Karpinska, Mohit Iyyer*2023 · 156 citations*](https://md.research.elamur.ai/free/en/papers/karpinska-2023-large-language-models-effectively-leverage/)
15. [**The Devil Is in the Errors: Leveraging Large Language Models for Fine-grained Machine Translation Evaluation**Patrick Fernandes, Daniel Deutsch, Mara Finkelstein, et al.*2023 · 156 citations*](https://md.research.elamur.ai/free/en/papers/fernandes-2023-devil-is-errors-leveraging-large/)
16. [**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/)
17. [**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/)
18. [**Scaling up CometKiwi: Unbabel-IST 2023 Submission for the Quality Estimation Shared Task**Ricardo Rei, Nuno M. Guerreiro, José Pombal, et al.*2023 · 135 citations*](https://md.research.elamur.ai/free/en/papers/rei-2023-scaling-up-cometkiwi-unbabel-ist/)
19. [**EuroLLM: Multilingual Language Models for Europe**Pedro Henrique Martins, Patrick Fernandes, Joao Alves, et al.*2024 · 131 citations*](https://md.research.elamur.ai/free/en/papers/martins-2024-eurollm-multilingual-language-models-europe/)
20. [**Findings of the WMT 2023 Shared Task on Quality Estimation**Frederic Blain, Chrysoula Zerva, Ricardo Rei, et al.*2023 · 129 citations*](https://md.research.elamur.ai/free/en/papers/blain-2023-findings-wmt-2023-shared-task/)
21. [**Deductive Verification of Chain-of-Thought Reasoning**Zhan Ling, Yunhao Fang, Xuanlin Li, et al.*2023 · 128 citations*](https://md.research.elamur.ai/free/en/papers/ling-2023-deductive-verification-chain-thought-reasoning/)
22. [**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/)
23. [**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/)
24. [**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/)
25. [**Findings of the WMT25 General Machine Translation Shared Task: Time to Stop Evaluating on Easy Test Sets**Tom Kocmi, Ekaterina Artemova, Eleftherios Avramidis, et al.*2025 · 73 citations*](https://md.research.elamur.ai/free/en/papers/kocmi-2025-findings-wmt25-general-machine-translation/)
26. [**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/)
27. [**Translating Step-by-Step: Decomposing the Translation Process for Improved Translation Quality of Long-Form Texts**Eleftheria Briakou, Jiaming Luo, Colin Cherry, et al.*2024 · 46 citations*](https://md.research.elamur.ai/free/en/papers/briakou-2024-translating-step-step-decomposing-translation/)
28. [**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/)
29. [**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/)
30. [**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/)
31. [**MQM-APE: Toward High-Quality Error Annotation Predictors with Automatic Post-Editing in LLM Translation Evaluators**Qingyu Lu, Liang Ding, Kanjian Zhang, et al.*2025 · 22 citations*](https://md.research.elamur.ai/free/en/papers/lu-2025-mqm-ape-high-quality-error/)
32. [**Benchmarking LLMs for Translating Classical Chinese Poetry: Evaluating Adequacy, Fluency, and Elegance**Andong Chen, Lianzhang Lou, Kehai Chen, et al.*2025 · 18 citations*](https://md.research.elamur.ai/free/en/papers/chen-2025-benchmarking-llms-translating-classical-chinese/)
33. [**Do Large Language Models Understand Word Senses?**Domenico Meconi, Simone Stirpe, Federico Martelli*2025 · 18 citations*](https://md.research.elamur.ai/free/en/papers/meconi-2025-llms-word-senses/)
34. [**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/)
35. [**TurBLiMP: A Turkish Benchmark of Linguistic Minimal Pairs**Ezgi Başar, Francesca Padovani, Jaap Jumelet, et al.*2025 · 14 citations*](https://md.research.elamur.ai/free/en/papers/basar-2025-turblimp-turkish-benchmark-linguistic-minimal/)
36. [**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/)
37. [**DiBiMT: A Gold Evaluation Benchmark for Studying Lexical Ambiguity in Machine Translation**Federico Martelli, Stefano Perrella, Niccolò Campolungo, et al.*2025 · 11 citations*](https://md.research.elamur.ai/free/en/papers/martelli-2025-dibimt-gold-evaluation-benchmark-studying/)
38. [**GrammaMT: Improving Machine Translation with Grammar-Informed In-Context Learning**Rita Ramos, Everlyn Asiko Chimoto, Maartje Ter Hoeve, et al.*2025 · 11 citations*](https://md.research.elamur.ai/free/en/papers/ramos-2025-grammamt-improving-machine-translation-grammar/)
39. [**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/)
40. [**HeSum: a Novel Dataset for Abstractive Text Summarization in Hebrew**Tzuf Paz-Argaman, Itai Mondshine, Asaf Achi Mordechai, et al.*2024 · 7 citations*](https://md.research.elamur.ai/free/en/papers/argaman-2024-hesum-novel-dataset-abstractive-text/)
41. [**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/)
42. [**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/)
43. [**The Landscape of Arabic Large Language Models (ALLMs): A New Era for Arabic Language Technology**Shahad Al-Khalifa; Nadir Durrani; Hend Al-Khalifa;, Firoj Alam*2025 · 4 citations*](https://md.research.elamur.ai/free/en/papers/al-khalifa-2025-landscape-arabic-large-language-models/)
44. [**Estonian WinoGrande Dataset: Comparative Analysis of LLM Performance on Human and Machine Translation**Marii Ojastu, Hele-Andra Kuulmets, Aleksei Dorkin, et al.*2026 · 3 citations*](https://md.research.elamur.ai/free/en/papers/ojastu-2026-estonian-winogrande-dataset-comparative-analysis/)
45. [**Gender Disambiguation in Machine Translation: Diagnostic Evaluation in Decoder-Only Architectures**Chiara Manna, Hosein Mohebbi, Afra Alishahi, et al.*2026 · 3 citations*](https://md.research.elamur.ai/free/en/papers/manna-2026-gender-disambiguation-machine-translation-diagnostic/)
46. [**Cyber Risks of Machine Translation Critical Errors : Arabic Mental Health Tweets as a Case Study**Hadeel Saadany, Ashraf Tantawy, Constantin Orasan*2024 · 3 citations*](https://md.research.elamur.ai/free/en/papers/saadany-2024-cyber-risks-machine-translation-critical/)
47. [**A Critical Study of Automatic Evaluation in Sign Language Translation**Shakib Yazdani, Yasser HAMIDULLAH, Cristina España-Bonet, et al.*2026 · 2 citations*](https://md.research.elamur.ai/free/en/papers/yazdani-2026-critical-study-automatic-evaluation-sign/)
48. [**AlexandriaX 2026: The First Shared Task on Dialectal Arabic Machine Translation**Abdellah El Mekki, AbdelRahim A. Elmadany, Samar M. Magdy, et al.*2026 · 2 citations*](https://md.research.elamur.ai/free/en/papers/mekki-2026-alexandriax-2026-first-shared-task/)
49. [**PHEB: An European Portuguese High School-Level LLM Benchmark**Diogo C. Tavares, Rafael Ferreira, Afonso Simplício, et al.*2026 · 2 citations*](https://md.research.elamur.ai/free/en/papers/tavares-2026-pheb-european-portuguese-high-school/)
50. [**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/)
51. [**When Flores Bloomz Wrong: Cross-Direction Contamination in Machine Translation Evaluation**David Tan, Pinzhen Chen, Josef van Genabith, et al.*2026 · 2 citations*](https://md.research.elamur.ai/free/en/papers/tan-2026-when-flores-bloomz-wrong-cross/)
52. [**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/)
53. [**Arabizi vs LLMs: Can the Genie Understand the Language of Aladdin?**Perla Al Almaoui, Pierrette Bouillon, Simon Hengchen*2025 · 2 citations*](https://md.research.elamur.ai/free/en/papers/almaoui-2025-arabizi-vs-llms-can-genie/)
54. [**A Pocket Offline Model for Simultaneous Speech Translation as CUNI Submission to IWSLT 2026**Aziz Sharipov Ortega, Dominik Macháček*2026 · 1 citation*](https://md.research.elamur.ai/free/en/papers/ortega-2026-pocket-offline-model-simultaneous-speech/)
55. [**Anchoring the Judge: Curriculum-Based Adaptation and Reference-Anchored MQM for LLM-Based Machine Translation of an Unseen Low-Resource Language - A Case of Nupe**Umar Baba Umar, Sulaimon Adebayo Bashir, Abdulmalik Danlami Mohammed*2026 · 1 citation*](https://md.research.elamur.ai/free/en/papers/umar-2026-anchoring-judge-curriculum-based-adaptation/)
56. [**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/)
57. [**BSC's Submission to the Instruction Following Track of IWSLT 2026**Oriol Pareras, Joan Llado, Pol Buitrago, et al.*2026 · 1 citation*](https://md.research.elamur.ai/free/en/papers/pareras-2026-bsc-s-submission-instruction-following/)
58. [**Can Linguistically Related Languages Guide LLM Translation in Low-Resource Settings?**Aishwarya Ramasethu, Rohin Garg, Niyathi Allu, et al.*2026 · 1 citation*](https://md.research.elamur.ai/free/en/papers/ramasethu-2026-can-linguistically-related-languages-guide/)
59. [**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/)
60. [**CUHKSZ Simultaneous Speech Translation System for IWSLT 2026**Zeyu Yang, Satoshi Nakamura*2026 · 1 citation*](https://md.research.elamur.ai/free/en/papers/yang-2026-cuhksz-simultaneous-speech-translation-system/)
61. [**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/)
62. [**MLLP-VRAIN UPV System for the IWSLT 2026 Simultaneous Speech Translation Task**Jorge Iranzo-Sánchez, Gerard Mas-Mollà, Adrià Gimenez, et al.*2026 · 1 citation*](https://md.research.elamur.ai/free/en/papers/sanchez-2026-mllp-vrain-upv-system-iwslt/)
63. [**Multilingual Long-Form Speech Instruction Following: KIT's Submission to IWSLT 2026**Enes Yavuz Ugan, Maike Züfle, Yuka Ko, et al.*2026 · 1 citation*](https://md.research.elamur.ai/free/en/papers/ugan-2026-multilingual-long-form-speech-instruction/)
64. [**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/)
65. [**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/)
66. [**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/)
67. [**Speak in Context: Multilingual ASR with Speech–Context Alignment via Contrastive Learning**Yuchen Zhang, Haralambos Mouratidis, Ravi Shekhar*2026 · 1 citation*](https://md.research.elamur.ai/free/en/papers/zhang-2026-speak-context-multilingual-asr-speech/)
68. [**Test-Time Adaptation of an Offline Multimodal Foundation Model for Simultaneous Speech Translation**Yi Xing, Manli Yu, Pengfei Liu, et al.*2026 · 1 citation*](https://md.research.elamur.ai/free/en/papers/xing-2026-test-time-adaptation-offline-multimodal/)
69. [**Towards Dynamic Attention Masking for Simultaneous Speech Translation**Benjamin Pong*2026 · 1 citation*](https://md.research.elamur.ai/free/en/papers/pong-2026-dynamic-attention-masking-simultaneous-speech/)
70. [**TTLab at AlexandriaX-2026: A Fine-Tuned Surface Tagger for Arabic Machine-Translation Error-Span Detection and Classification**Ali Abusaleh, Bhuvanesh Verma, Alexander Mehler*2026 · 1 citation*](https://md.research.elamur.ai/free/en/papers/abusaleh-2026-ttlab-alexandriax-2026-fine-tuned/)
71. [**When Translations Surprise: Human Awareness of Predictability in Translations**Cristian García-Romero, Miquel Esplà-Gomis, Felipe Sanchez-Martinez*2026 · 1 citation*](https://md.research.elamur.ai/free/en/papers/romero-2026-when-translations-surprise-human-awareness/)
72. [**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/)
73. [**A Fine-Grained Linguistic Evaluation of Low-Resource Luxembourgish–English MT**Nils Rehlinger*2026*](https://md.research.elamur.ai/free/en/papers/rehlinger-2026-fine-grained-linguistic-evaluation-low/)
74. [**A Multilingual Red Teaming–Driven Safety Analysis of LLMs**Patrícia Pandeiro, Vera Cabarrão, Helena Moniz*2026*](https://md.research.elamur.ai/free/en/papers/pandeiro-2026-multilingual-red-teaming-driven-safety/)
75. [**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/)
76. [**A Single Model Ensemble Framework for Neural Machine Translation Using Pivot Translation**Seokjin Oh, Keonwoong Noh, Woohwan Jung*2026*](https://md.research.elamur.ai/free/en/papers/oh-2026-single-model-ensemble-framework-neural/)
77. [**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/)
78. [**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/)
79. [**Data-Centric Approach at the LoResMT 2026 Turkic Translation Challenge: Russian-Kyrgyz**Dmitry Novokshanov*2026*](https://md.research.elamur.ai/free/en/papers/novokshanov-2026-data-centric-approach-loresmt-2026/)
80. [**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/)
81. [**Diagnosing Translated Benchmarks: An Automated Quality Assurance Study of the EU20 Benchmark Suite**Klaudia Thellmann, Bernhard Stadler, Michael Färber*2026*](https://md.research.elamur.ai/free/en/papers/thellmann-2026-diagnosing-translated-benchmarks-automated-quality/)
82. [**EIFFEL: a novel benchmark to measure bias of English heavy training on French idiomatic expressions**Charlotte Noel, Nicholas Asher, Olivier Gouvert, et al.*2026*](https://md.research.elamur.ai/free/en/papers/noel-2026-eiffel-novel-benchmark-measure-bias/)
83. [**Embedding Similarity Is Not Quality Estimation: Lessons from Replacing a Dedicated QE Model**Dimitrios Zaikis, Andrea Biondo, Matthew Dixon, et al.*2026*](https://md.research.elamur.ai/free/en/papers/zaikis-2026-embedding-similarity-is-not-quality/)
84. [**Evaluating Native-Speaker Preferences on Machine Translation and Post-Edits for Five African Languages**Hiba El Oirghi, Tajuddeen Gwadabe, Marine Carpuat*2026*](https://md.research.elamur.ai/free/en/papers/oirghi-2026-evaluating-native-speaker-preferences-machine/)
85. [**Fine-tuning Whisper with Spontaneous Persian Speech (SPS)**Behnoosh Namdarzadeh, Nicolas Ballier*2026*](https://md.research.elamur.ai/free/en/papers/namdarzadeh-2026-fine-tuning-whisper-spontaneous-persian/)
86. [**Hindsight Quality Prediction Experiments in Multi-Candidate Human-Post-Edited Machine Translation**Malik Marmonier, Benoît Sagot, Rachel Bawden*2026*](https://md.research.elamur.ai/free/en/papers/marmonier-2026-hindsight-quality-prediction-experiments-multi/)
87. [**I Understand How You Feel: Enhancing Deeper Emotional Support Through Multilingual Emotional Validation in Dialogue System**Zi Haur Pang, Yahui Fu, Koji Inoue, et al.*2026*](https://md.research.elamur.ai/free/en/papers/pang-2026-i-understand-how-you-feel/)
88. [**Interlinear Glosses as a Multilingual Pivot for Machine Translation: An Updated Study on Turkish with Restricted Resources**Volkan Ozer, Shu Okabe, Alexander Fraser*2026*](https://md.research.elamur.ai/free/en/papers/ozer-2026-interlinear-glosses-as-multilingual-pivot/)
89. [**Machine translation Evaluation Eng-Thai MQM Ranking dataset**Phichet Phuangrot, Natdanai Trintawat, Kanawat Vilasri, et al.*2026*](https://md.research.elamur.ai/free/en/papers/phuangrot-2026-machine-translation-evaluation-eng-thai/)
90. [**MQM Re-Annotation: A Technique for Collaborative Evaluation of Machine Translation**Parker Riley, Daniel Deutsch, Mara Finkelstein, et al.*2026*](https://md.research.elamur.ai/free/en/papers/riley-2026-mqm-re-annotation-technique-collaborative/)
91. [**Multi-Agent Debate for Machine Translation: A Case Study on English-Japanese Translation**Zhan Shen, Jason Naradowsky, Xiaotian Wang, et al.*2026*](https://md.research.elamur.ai/free/en/papers/shen-2026-multi-agent-debate-machine-translation/)
92. [**Multilingual KokoroChat: A Multi-LLM Ensemble Translation Method for Creating a Multilingual Counseling Dialogue Dataset**Ryoma Suzuki, Zhiyang Qi, Michimasa Inaba*2026*](https://md.research.elamur.ai/free/en/papers/suzuki-2026-multilingual-kokorochat-multi-llm-ensemble/)
93. [**On Temperature-Constrained Non-Deterministic Machine Translation: Potential and Evaluation**Weichuan Wang, Mingyang Liu, Chen Ma, et al.*2026*](https://md.research.elamur.ai/free/en/papers/wang-2026-temperature-constrained-non-deterministic-machine/)
94. [**One Size Does Not Fit All: Why EU Legislative Translation Demands Domain-Specific Fine-Tuning of LLMs**Valerio Lorini, Paula Vlaic, Ulascan Akbulut, et al.*2026*](https://md.research.elamur.ai/free/en/papers/lorini-2026-one-size-does-not-fit/)
95. [**Predict and Fix: A Unified Model for Translation Quality Estimation and Post-Editing**Maciej Modrzejewski, Yash Bhaskar, Chinmay Pateria*2026*](https://md.research.elamur.ai/free/en/papers/modrzejewski-2026-predict-fix-unified-model-translation/)
96. [**Quantifying the Impact of Translation Errors on Multilingual LLM Evaluation**Klaudia Thellmann, Bernhard Stadler, Michael Färber, et al.*2026*](https://md.research.elamur.ai/free/en/papers/thellmann-2026-quantifying-impact-translation-errors-multilingual/)
97. [**Reading Time in the Wild: An Assessment of Readability Predictors Based on Naturally-Observed Reading Times**Sijbren van Vaals, Rik van Noord, Malvina Nissim*2026*](https://md.research.elamur.ai/free/en/papers/vaals-2026-reading-time-wild-assessment-readability/)
98. [**Redefining Machine Simultaneous Interpretation: From Incremental Translation to Human-Like Strategies**Qianen Zhang, Zeyu Yang, Satoshi Nakamura*2026*](https://md.research.elamur.ai/free/en/papers/zhang-2026-redefining-machine-simultaneous-interpretation-incremental/)
99. [**Rethinking Gender Annotation for Bias Evaluation in Machine Translation: Can LLMs Improve Reliability?**Chiara Manna, Argentina Anna Rescigno, Eva Vanmassenhove*2026*](https://md.research.elamur.ai/free/en/papers/manna-2026-rethinking-gender-annotation-bias-evaluation/)
100. [**Scoring the Translation: On Target Automatic Keyword-Based Evaluation of Machine Translation in the Sports Domain**Steinþór Steingrímsson, Einar Freyr Sigurðsson*2026*](https://md.research.elamur.ai/free/en/papers/steingrimsson-2026-scoring-translation-target-automatic-keyword/)

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