---
title: "Who cites Experts, Errors, and Context: A Large-Scale…"
description: "The papers of the Elamur Research library that cite «Experts, Errors, and Context: A Large-Scale Study of Human Evaluation for Machine Translation», found…"
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# Who cites «Experts, Errors, and Context: A Large-Scale Study of Human Evaluation for Machine Translation»

395 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/freitag-2021-experts-errors-context-large-scale/)

Pages: **1** · [2](https://md.research.elamur.ai/free/en/papers/freitag-2021-experts-errors-context-large-scale/cited-by/page/2/) · [3](https://md.research.elamur.ai/free/en/papers/freitag-2021-experts-errors-context-large-scale/cited-by/page/3/) · [4](https://md.research.elamur.ai/free/en/papers/freitag-2021-experts-errors-context-large-scale/cited-by/page/4/)

1. [$\tau$-Multilingual: Benchmarking Voice Agents Across Languages](https://arxiv.org/abs/2609.35820) *— 2026 · arXiv:2609.35820*
2. [Assessing Quality of Experience in Natural Language Generation of German Text](https://arxiv.org/abs/2608.18888) *— 2026 · arXiv:2608.18888*
3. [Automated evaluation of LLMs for effective machine translation of Mandarin Chinese to English](https://arxiv.org/abs/2603.09998) *— 2026 · arXiv:2603.09998*
4. [Benchmarking Speech-to-Speech Translation Models](https://arxiv.org/abs/2606.03241) *— 2026 · arXiv:2606.03241*
5. [Beyond BLEU: A Case for Redefining Sign Language Translation Benchmarks](https://arxiv.org/abs/2609.03734) *— 2026 · arXiv:2609.03734*
6. [Beyond Literal Mapping: Benchmarking and Improving Non-Literal Translation Evaluation](https://aclanthology.org/2026.acl-long.205/) *— 2026 · Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
7. [Can We Triage LLM Translation Errors in Classical Texts Without Human References? Source Novelty, GEMBA Scoring, and Budgeted Review through Pali-to-English Translation](https://arxiv.org/abs/2609.14963) *— 2026 · arXiv:2609.14963*
8. [Contrastive ESA: Human Evaluation of Multiple Translations at Once](https://arxiv.org/abs/2607.26640) *— 2026 · arXiv:2607.26640*
9. [Diagnose, Then Repair: A Two-Stage MQM-Guided Post-Editing Framework for Domain-Specific Machine Translation](https://aclanthology.org/2026.acl-industry.115/) *— 2026 · Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 6: Industry Track)*
10. [Evaluating Communicative Success in Machine-Translated Conversation](https://arxiv.org/abs/2609.19885) *— 2026 · arXiv:2609.19885*
11. [Evaluating LLM-Based Translation of a Low-Resource Technical Language: The Medical and Philosophical Greek of Galen](https://arxiv.org/abs/2602.24119) *— 2026 · arXiv:2602.24119*
12. [FINEST: Improving LLM Responses to Sensitive Topics Through Fine-Grained Evaluation](https://aclanthology.org/2026.findings-eacl.327/) *— 2026 · Findings of the Association for Computational Linguistics: EACL 2026*
13. [FairQE: Multi-Agent Framework for Mitigating Gender Bias in Translation Quality Estimation](https://aclanthology.org/2026.acl-long.1757/) *— 2026 · Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
14. [From Outliers to Errors: Auditing Pali-to-English LLM Translations with Multi-Reference Adjudication](https://arxiv.org/abs/2606.01136) *— 2026 · arXiv:2606.01136*
15. [Generating Difficult-to-Translate Texts](https://aclanthology.org/2026.mme-main.14/) *— 2026 · Proceedings of the First Workshop on Multilingual Multicultural Evaluation*
16. [Hearing to Translate: The Effectiveness of Speech Modality Integration into LLMs](https://aclanthology.org/2026.tacl-1.89/) *— 2026 · Transactions of the Association for Computational Linguistics*
17. [In the Blind: Building Pseudo-References for MT Evaluation](https://arxiv.org/abs/2609.13611) *— 2026 · arXiv:2609.13611*
18. [IndicQE-APE: A Consolidated Benchmark for Quality Estimation and Automatic Post-Editing for Indic Languages](https://arxiv.org/abs/2608.16344) *— 2026 · arXiv:2608.16344*
19. [Is Human Annotation Necessary? Iterative MBR Distillation for Error Span Detection in Machine Translation](https://arxiv.org/abs/2603.12983) *— 2026 · arXiv:2603.12983*
20. [JP-TL-Bench: Anchored Pairwise LLM Evaluation for Bidirectional Japanese-English Translation](https://arxiv.org/abs/2601.00223) *— 2026 · arXiv:2601.00223*
21. [LLM as a Meta-Judge: Synthetic Data for NLP Evaluation Metric Validation](https://aclanthology.org/2026.acl-srw.125/) *— 2026 · Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 4: Student Research Workshop)*
22. [LLM-as-a-Jury for Machine Translation Publishability Assessment](https://aclanthology.org/2026.eamt-1.7/) *— 2026 · Proceedings of the 26th Annual Conference of the European Association for Machine Translation (Volume 1)*
23. [LLM-as-a-qualitative-judge: automating error analysis in natural language generation](https://aclanthology.org/2026.mme-main.7/) *— 2026 · Proceedings of the First Workshop on Multilingual Multicultural Evaluation*
24. [LLMs as Span Annotators: A Comparative Study of LLMs and Humans](https://aclanthology.org/2026.mme-main.1/) *— 2026 · Proceedings of the First Workshop on Multilingual Multicultural Evaluation*
25. [LLMs in the Real World: Evaluating “AI” in Emergency Contexts](https://aclanthology.org/2026.findings-acl.1779/) *— 2026 · Findings of the Association for Computational Linguistics: ACL 2026*
26. [LQM: Linguistically Motivated Multidimensional Quality Metrics for Machine Translation](https://aclanthology.org/2026.findings-acl.2012/) *— 2026 · Findings of the Association for Computational Linguistics: ACL 2026*
27. [Large Language Models as Annotators for Machine Translation Quality Estimation](https://arxiv.org/abs/2603.10775) *— 2026 · arXiv:2603.10775*
28. [Last Translation Benchmark](https://arxiv.org/abs/2609.04173) *— 2026 · arXiv:2609.04173*
29. [LocQE: Principled Domain Adaptation for Localisation Quality Estimation by Leveraging Post-Edits](https://arxiv.org/abs/2609.18720) *— 2026 · arXiv:2609.18720*
30. [MAPS: A Multilingual Benchmark for Agent Performance and Security](https://aclanthology.org/2026.findings-eacl.42/) *— 2026 · Findings of the Association for Computational Linguistics: EACL 2026*
31. [MQM Re-Annotation: A Technique for Collaborative Evaluation of Machine Translation](https://aclanthology.org/2026.acl-long.1553/) *— 2026 · Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
32. [Machine translation Evaluation Eng-Thai MQM Ranking dataset](https://aclanthology.org/2026.eacl-short.41/) *— 2026 · Proceedings of the 19th Conference of the European Chapter of the Association for Computational Linguistics (Volume 2: Short Papers)*
33. [MetaDocEval: A Contrastive Framework for Evaluating Machine Translation Metrics at the Document-Level](https://aclanthology.org/2026.eamt-1.19/) *— 2026 · Proceedings of the 26th Annual Conference of the European Association for Machine Translation (Volume 1)*
34. [Mind Which Bird You Favour: Parameterizing Adequacy-Fluency Balance in Meta-Evaluation of Machine Translation](https://arxiv.org/abs/2609.14795) *— 2026 · arXiv:2609.14795*
35. [Multi-Agent Debate for Machine Translation: A Case Study on English-Japanese Translation](https://aclanthology.org/2026.eamt-1.16/) *— 2026 · Proceedings of the 26th Annual Conference of the European Association for Machine Translation (Volume 1)*
36. [Multi-modal, Multi-task, Multi-criteria Automatic Evaluation with Vision Language Models](https://aclanthology.org/2026.lrec-1.738/) *— 2026 · Proceedings of the Fifteenth Language Resources and Evaluation Conference*
37. [PEAR: Pairwise Evaluation for Automatic Relative Scoring in Machine Translation](https://aclanthology.org/2026.acl-long.1953/) *— 2026 · Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
38. [Pearmut: Human Evaluation of Translation Made Trivial](https://arxiv.org/abs/2601.02933) *— 2026 · arXiv:2601.02933*
39. [Quantifying the Impact of Translation Errors on Multilingual LLM Evaluation](https://aclanthology.org/2026.acl-long.1916/) *— 2026 · Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
40. [R1-T1: Fully Incentivizing Translation Capability in LLMs via Reasoning Learning](https://aclanthology.org/2026.tacl-1.95/) *— 2026 · Transactions of the Association for Computational Linguistics*
41. [Referenceless Evaluation of Machine Translation Models by Ranking Performance in Romanian to English Translate-train Settings](https://aclanthology.org/2026.lrec-1.693/) *— 2026 · Proceedings of the Fifteenth Language Resources and Evaluation Conference*
42. [Register Sensitivity in Scalar MT Evaluation: Evidence from Spanish–Basque Informal Discourse](https://aclanthology.org/2026.sigul-1.2/) *— 2026 · Proceedings of the SIGUL 2026 Joint Workshop with ELE, EURALI, and DCLRL: Towards Inclusivity and Equality: Language Resources and Technologies for Under-Resourced and Endangered Languages*
43. [Remedy-R: Generative Reasoning for Machine Translation Evaluation without Error Annotations](https://aclanthology.org/2026.findings-acl.364/) *— 2026 · Findings of the Association for Computational Linguistics: ACL 2026*
44. [RouteMoA: Dynamic Routing without Pre-Inference Boosts Efficient Mixture-of-Agents](https://aclanthology.org/2026.acl-long.558/) *— 2026 · Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
45. [Rubric-as-Experts: Case-Specific MQM Rubrics for Translation Error Span Detection](https://arxiv.org/abs/2606.21559) *— 2026 · arXiv:2606.21559*
46. [Should We be Pedantic About Reasoning Errors in Machine Translation?](https://arxiv.org/abs/2604.09890) *— 2026 · arXiv:2604.09890*
47. [SiniticMTError: A Machine Translation Dataset with Error Annotations for Sinitic Languages](https://aclanthology.org/2026.lrec-1.683/) *— 2026 · Proceedings of the Fifteenth Language Resources and Evaluation Conference*
48. [Span-Level Machine Translation Meta-Evaluation](https://arxiv.org/abs/2603.19921) *— 2026 · arXiv:2603.19921*
49. [SwissGov-RSD: A Human-annotated, Cross-lingual Benchmark for Token-level Recognition of Semantic Differences Between Related Documents](https://aclanthology.org/2026.acl-long.1437/) *— 2026 · Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
50. [TQLite: Multi-LLM Jury Guided Distillation for Real-time MQM Translation Quality Evaluation](https://arxiv.org/abs/2608.02975) *— 2026 · arXiv:2608.02975*
51. [TTLab at AlexandriaX-2026: A Fine-Tuned Surface Tagger for Arabic Machine-Translation Error-Span Detection and Classification](https://arxiv.org/abs/2609.29633) *— 2026 · arXiv:2609.29633*
52. [The Blindness of Document-Level Translation Evaluation](https://arxiv.org/abs/2609.05949) *— 2026 · arXiv:2609.05949*
53. [The MaTOS Pipeline for the Translation of Scientific Abstracts on the HAL Platform](https://aclanthology.org/2026.eamt-2.30/) *— 2026 · Proceedings of the 26th Annual Conference of the European Association for Machine Translation (Volume 2)*
54. [To Write or to Automate Linguistic Prompts, That Is the Question](https://aclanthology.org/2026.eamt-1.8/) *— 2026 · Proceedings of the 26th Annual Conference of the European Association for Machine Translation (Volume 1)*
55. [Toward domain-specific machine translation and quality estimation systems](https://arxiv.org/abs/2603.24955) *— 2026 · arXiv:2603.24955*
56. [Translation-CoT: A Human-Inspired Chain-of-Thought Framework for Multilingual LLM Translation](https://aclanthology.org/2026.amta-research.2/) *— 2026 · Proceedings of the 17th Conference of the Association for Machine Translation in the Americas (Volume 1: Research Track)*
57. [Translators” Perceptions and Edit Traces: Quality of MT as a Tool in Canadian Parliamentary Translation](https://aclanthology.org/2026.amta-research.10/) *— 2026 · Proceedings of the 17th Conference of the Association for Machine Translation in the Americas (Volume 1: Research Track)*
58. [Using Model Disagreement to Identify Unstable Regions in MT Evaluation](https://aclanthology.org/2026.eamt-1.22/) *— 2026 · Proceedings of the 26th Annual Conference of the European Association for Machine Translation (Volume 1)*
59. [What Does LLM Refinement Actually Improve? A Systematic Study on Document-Level Literary Translation](https://aclanthology.org/2026.acl-long.268/) *— 2026 · Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
60. [When the Gold Standard Isn”t Necessarily Standard: Challenges of Evaluating the Translation of User-Generated Content](https://aclanthology.org/2026.eamt-1.30/) *— 2026 · Proceedings of the 26th Annual Conference of the European Association for Machine Translation (Volume 1)*
61. [Who Watches the Watchmen? Humans Disagree With Translation Metrics on Unseen Domains](https://aclanthology.org/2026.findings-acl.1145/) *— 2026 · Findings of the Association for Computational Linguistics: ACL 2026*
62. [XQ-MEval: A Dataset with Cross-lingual Parallel Quality for Benchmarking Translation Metrics](https://aclanthology.org/2026.findings-acl.1846/) *— 2026 · Findings of the Association for Computational Linguistics: ACL 2026*
63. [XToM: Exploring the Multilingual Theory of Mind for Large Language Models](https://aclanthology.org/2026.acl-long.805/) *— 2026 · Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
64. [“Be My Cheese?”: Cultural Nuance Benchmarking for Machine Translation in Multilingual LLMs](https://aclanthology.org/2026.gem-main.6/) *— 2026 · Proceedings of the Fifth Workshop on Generation, Evaluation and Metrics (GEM)*
65. [A comparison of translation performance between DeepL and Supertext](https://aclanthology.org/2025.mtsummit-2.6/) *— 2025 · Proceedings of Machine Translation Summit XX: Volume 2*
66. [AI agents may be worth the hype but not the resources (yet): An initial exploration of machine translation quality and costs in three language pairs in the legal and news domains](https://arxiv.org/abs/2505.01560) *— 2025 · arXiv:2505.01560*
67. [AI-Assisted Human Evaluation of Machine Translation](https://aclanthology.org/2025.naacl-long.255/) *— 2025 · Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers)*
68. [Align-then-Slide: A complete evaluation framework for Ultra-Long Document-Level Machine Translation](https://arxiv.org/abs/2509.03809) *— 2025 · arXiv:2509.03809*
69. [Aligning Black-box Language Models with Human Judgments](https://aclanthology.org/2025.findings-naacl.376/) *— 2025 · Findings of the Association for Computational Linguistics: NAACL 2025*
70. [Alleviating Distribution Shift in Synthetic Data for Machine Translation Quality Estimation](https://aclanthology.org/2025.acl-long.373/) *— 2025 · Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
71. [An Empirical Analysis of Machine Translation for Expanding Multilingual Benchmarks](https://aclanthology.org/2025.wmt-1.1/) *— 2025 · Proceedings of the Tenth Conference on Machine Translation*
72. [An Evaluation Resource for Grounding Translation Errors](https://aclanthology.org/2025.findings-emnlp.1299/) *— 2025 · Findings of the Association for Computational Linguistics: EMNLP 2025*
73. [An Interdisciplinary Approach to Human-Centered Machine Translation](https://aclanthology.org/2025.emnlp-main.1164/) *— 2025 · Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing*
74. [Analyzing and Evaluating Correlation Measures in NLG Meta-Evaluation](https://aclanthology.org/2025.naacl-long.111/) *— 2025 · Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers)*
75. [Are Large Reasoning Models Good Translation Evaluators? Analysis and Performance Boost](https://arxiv.org/abs/2510.20780) *— 2025 · arXiv:2510.20780*
76. [Ask Me Like I”m Human: LLM-based Evaluation with For-Human Instructions Correlates Better with Human Evaluations than Human Judges](https://aclanthology.org/2025.trl-1.9/) *— 2025 · Proceedings of the 4th Table Representation Learning Workshop*
77. [AskQE: Question Answering as Automatic Evaluation for Machine Translation](https://aclanthology.org/2025.findings-acl.899/) *— 2025 · Findings of the Association for Computational Linguistics: ACL 2025*
78. [Audio-Based Crowd-Sourced Evaluation of Machine Translation Quality](https://aclanthology.org/2025.wmt-1.3/) *— 2025 · Proceedings of the Tenth Conference on Machine Translation*
79. [Automatic Input Rewriting Improves Translation with Large Language Models](https://aclanthology.org/2025.naacl-long.542/) *— 2025 · Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers)*
80. [COMET-poly: Machine Translation Metric Grounded in Other Candidates](https://aclanthology.org/2025.wmt-1.63/) *— 2025 · Proceedings of the Tenth Conference on Machine Translation*
81. [CSEval: Towards Automated, Multi-Dimensional, and Reference-Free Counterspeech Evaluation using Auto-Calibrated LLMs](https://aclanthology.org/2025.naacl-long.279/) *— 2025 · Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers)*
82. [Calibrating Translation Decoding with Quality Estimation on LLMs](https://arxiv.org/abs/2504.19044) *— 2025 · arXiv:2504.19044*
83. [Can LLMs Help Sun Wukong in his Journey to the West? A Case Study of Language Models in Video Game Localization](https://aclanthology.org/2025.lm4dh-1.16/) *— 2025 · Proceedings of the First Workshop on Natural Language Processing and Language Models for Digital Humanities*
84. [Command-A-Translate: Raising the Bar of Machine Translation with Difficulty Filtering](https://aclanthology.org/2025.wmt-1.55/) *— 2025 · Proceedings of the Tenth Conference on Machine Translation*
85. [Context-Aware Monolingual Evaluation of Machine Translation](https://aclanthology.org/2025.mtsummit-1.11/) *— 2025 · Proceedings of Machine Translation Summit XX: Volume 1*
86. [Context-Aware Monolingual Human Evaluation of Machine Translation](https://arxiv.org/abs/2504.07685) *— 2025 · arXiv:2504.07685*
87. [Contextual Metric Meta-Evaluation by Measuring Local Metric Accuracy](https://aclanthology.org/2025.findings-naacl.276/) *— 2025 · Findings of the Association for Computational Linguistics: NAACL 2025*
88. [ContrastScore: Towards Higher Quality, Less Biased, More Efficient Evaluation Metrics with Contrastive Evaluation](https://aclanthology.org/2025.ijcnlp-long.163/) *— 2025 · Proceedings of the 14th International Joint Conference on Natural Language Processing and the 4th Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics*
89. [Cross-lingual Human-Preference Alignment for Neural Machine Translation with Direct Quality Optimization](https://aclanthology.org/2025.wmt-1.2/) *— 2025 · Proceedings of the Tenth Conference on Machine Translation*
90. [Crosslingual Optimized Metric for Translation Assessment of Indian Languages](https://arxiv.org/abs/2509.17667) *— 2025 · arXiv:2509.17667*
91. [D\”ejà Vu: Multilingual LLM Evaluation through the Lens of Machine Translation Evaluation](https://arxiv.org/abs/2504.11829) *— 2025 · arXiv:2504.11829*
92. [DiBiMT: A Gold Evaluation Benchmark for Studying Lexical Ambiguity in Machine Translation](https://aclanthology.org/2025.cl-2.1/) *— 2025 · Computational Linguistics*
93. [Do Large Language Models understand how to be judges?](https://aclanthology.org/2025.luhme-1.9/) *— 2025 · Proceedings of the 2nd LUHME Workshop*
94. [Don”t Sweat the Small Stuff: Segment-Level Meta-Evaluation Based on Pairwise Difference Correlation](https://aclanthology.org/2025.emnlp-main.1273/) *— 2025 · Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing*
95. [Enhancing Human Evaluation in Machine Translation with Comparative Judgement](https://aclanthology.org/2025.acl-long.1002/) *— 2025 · Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
96. [Enhancing Human Evaluation in Machine Translation with Comparative Judgment](https://arxiv.org/abs/2502.17797) *— 2025 · arXiv:2502.17797*
97. [Enhancing Machine Translation with Self-Supervised Preference Data](https://aclanthology.org/2025.acl-long.1165/) *— 2025 · Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
98. [Estimating Machine Translation Difficulty](https://aclanthology.org/2025.findings-emnlp.1317/) *— 2025 · Findings of the Association for Computational Linguistics: EMNLP 2025*
99. [Evaluating Evaluation Metrics for Ancient Chinese to English Machine Translation](https://aclanthology.org/2025.alp-1.9/) *— 2025 · Proceedings of the Second Workshop on Ancient Language Processing*
100. [Evaluating Language Translation Models by Playing Telephone](https://aclanthology.org/2025.emnlp-main.524/) *— 2025 · Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing*

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