mlsanityData to 7 Oct 2026

BOUQuET: dataset, Benchmark and Open initiative for Universal Quality Evaluation in Translation

arXiv 2502.04314 ↗First posted 6 Feb 2025cs.CLcited by 21

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Abstract (arXiv)

BOUQuET is a multi-way, multicentric and multi-register/domain dataset and benchmark, and a broader collaborative initiative. This dataset is handcrafted in 8 non-English languages. Each of these source languages are representative of the most widely spoken ones and therefore they have the potential to serve as pivot languages that will enable more accurate translations. The dataset is multicentric to enforce representation of multilingual language features. In addition, the dataset goes beyond the sentence level, as it is organized in paragraphs of various lengths. Compared with related machine translation datasets, we show that BOUQuET has a broader representation of domains while simplifying the translation task for non-experts. Therefore, BOUQuET is specially suitable for crowd-source extension for which we are launching a call aiming at collecting a multi-way parallel corpus covering any written language.

Key facts. Cited by 21 papers in the map (data through 7 Oct 2026). Builds on 23 of its 51 references that are in the map. First posted on arXiv 6 Feb 2025.

Builds on

23 of 51 references.

References · 23

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11 more
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Citing papers per year: 2025: 2; 2026: 19.

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  1. 2026Scaling Model and Data for Multilingual Machine Translation with Open Large Language Modelscited by 4
  2. 2026RouteLMT: Learned Sample Routing for Hybrid LLM Translation Deploymentcited by 2
  3. 2026OmnilingualGAIA2: Evaluating the Multilingual Gap in Frontier AI Agentscited by 2
  4. 2025ChiKhaPo: A Large-Scale Multilingual Benchmark for Evaluating Lexical Comprehension and Generation in Large Language Modelscited by 1
  5. 2026Translation Asymmetry in LLMs as a Data Augmentation Factor: A Case Study for 6 Romansh Language Varietiescited by 1
  6. 2026Beyond "To whom it may concern": Tailoring Machine Translation to Audience and Intentcited by 1
  7. 2026OpenBibleTTS: Large-Scale Speech Resources and TTS Models for Low-Resource Languagescited by 1
  8. 2026ALEE: Any-Language Evaluation of Embeddings via English-Centric Minimal Pairscited by 1
  9. 2026Cultivar: A Contrastive and Locale-Oriented Translation Benchmark for Investigating Contamination and Localisation Robustnesscited by 1
  10. 2026Last Translation Benchmarkcited by 1
  11. 2025HEAD-QA v2: Expanding a Healthcare Benchmark for Reasoningcited by 0
  12. 2026ReBeCA: Unveiling Interpretable Behavior Hierarchy behind the Iterative Self-Reflection of Language Models with Causal Analysiscited by 0
9 more
  1. 2026Dialects of Translationese Shape Language Model Learningcited by 0
  2. 2026Model-Based Quality Assessment for Massively Multilingual Parallel Datacited by 0
  3. 2026Want Better Synthetic Data? Steer It: Activation Steering for Low-Resource Language Generationcited by 0
  4. 2026There is No Theoretical Curse of Multilinguality For Embedding Space Structurecited by 0
  5. 2026Cross-Lingual Alignment Without Joint Training: Do Monolingual Language Models Converge on Universal Representations?cited by 0
  6. 2026The University of Melbourne WMT 2026 CreoleMT Submission: A Domain-Balanced Approach to Low-Resource Pacific Creole Machine Translationcited by 0
  7. 2026ReMova: Fine-tuning LLMs for English to Belarusian translationcited by 0
  8. 2026LocQE: Principled Domain Adaptation for Localisation Quality Estimation by Leveraging Post-Editscited by 0
  9. 2026Precision over Scale: A Polish-Silesian Benchmark and a Translation System Outperforming Open-Source and Commercial Modelscited by 0