NusaX: Multilingual Parallel Sentiment Dataset for 10 Indonesian Local Languages
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Abstract (arXiv)
Natural language processing (NLP) has a significant impact on society via technologies such as machine translation and search engines. Despite its success, NLP technology is only widely available for high-resource languages such as English and Chinese, while it remains inaccessible to many languages due to the unavailability of data resources and benchmarks. In this work, we focus on developing resources for languages in Indonesia. Despite being the second most linguistically diverse country, most languages in Indonesia are categorized as endangered and some are even extinct. We develop the first-ever parallel resource for 10 low-resource languages in Indonesia. Our resource includes datasets, a multi-task benchmark, and lexicons, as well as a parallel Indonesian-English dataset. We provide extensive analyses and describe the challenges when creating such resources. We hope that our work can spark NLP research on Indonesian and other underrepresented languages.
Key facts. Cited by 67 papers in the map (data through 7 Oct 2026). Builds on 30 of its 85 references that are in the map. First posted on arXiv 31 May 2022.
Builds on
30 of 85 references.
References · 30
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- 2021Samanantar: The Largest Publicly Available Parallel Corpora Collection for 11 Indic Languagescited by 133
- 2020IndoNLU: Benchmark and Resources for Evaluating Indonesian Natural Language Understandingcited by 108
- 2020GLUECoS : An Evaluation Benchmark for Code-Switched NLPcited by 101
- 2021Language Models are Few-shot Multilingual Learnerscited by 92
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- 2019The FLoRes Evaluation Datasets for Low-Resource Machine Translation: Nepali-English and Sinhala-Englishcited by 61
- 2020IndoLEM and IndoBERT: A Benchmark Dataset and Pre-trained Language Model for Indonesian NLPcited by 57
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- 2021BiToD: A Bilingual Multi-Domain Dataset For Task-Oriented Dialogue Modelingcited by 55
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- 2021IndoNLI: A Natural Language Inference Dataset for Indonesiancited by 24
- 2020Improving Bi-LSTM Performance for Indonesian Sentiment Analysis Using Paragraph Vectorcited by 18
- 2020Towards Computational Linguistics in Minangkabau Language: Studies on Sentiment Analysis and Machine Translationcited by 16
- 2020Semi-Supervised Low-Resource Style Transfer of Indonesian Informal to Formal Language with Iterative Forward-Translationcited by 4
- 2020Plan Optimization to Bilingual Dictionary Induction for Low-Resource Language Familiescited by 3
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Citing papers per year: 2022: 3; 2023: 20; 2024: 18; 2025: 17; 2026: 9.
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- 2023Large Language Models Only Pass Primary School Exams in Indonesia: A Comprehensive Test on IndoMMLU7 Oct 2023
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- 2026Beyond Transfer Accuracy: Mechanism-Guided Controlled Adaptation for Low-Resource Languages13 Jan 2026
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