mlsanityData to 14 Oct 2026

LLM-powered Data Augmentation for Enhanced Cross-lingual Performance

arXiv 2305.14288 ↗First posted 23 May 2023cs.CLcited by 51

On the map: LLM reasoning → Reasoning benchmarks and evaluation

Abstract (arXiv)

This paper explores the potential of leveraging Large Language Models (LLMs) for data augmentation in multilingual commonsense reasoning datasets where the available training data is extremely limited. To achieve this, we utilise several LLMs, namely Dolly-v2, StableVicuna, ChatGPT, and GPT-4, to augment three datasets: XCOPA, XWinograd, and XStoryCloze. Subsequently, we evaluate the effectiveness of fine-tuning smaller multilingual models, mBERT and XLMR, using the synthesised data. We compare the performance of training with data generated in English and target languages, as well as translated English-generated data, revealing the overall advantages of incorporating data generated by LLMs, e.g. a notable 13.4 accuracy score improvement for the best case. Furthermore, we conduct a human evaluation by asking native speakers to assess the naturalness and logical coherence of the generated examples across different languages. The results of the evaluation indicate that LLMs such as ChatGPT and GPT-4 excel at producing natural and coherent text in most languages, however, they struggle to generate meaningful text in certain languages like Tamil. We also observe that ChatGPT falls short in generating plausible alternatives compared to the original dataset, whereas examples from GPT-4 exhibit competitive logical consistency.

Key facts. Cited by 51 papers in the map (data through 14 Oct 2026). Placed in Reasoning benchmarks and evaluation, one of 17 directions in LLM reasoning. Builds on 28 of its 43 references that are in the map. First posted on arXiv 23 May 2023.

Builds on

28 of 43 references.

Closest ancestors · 1

Same direction, newest first

  1. 2023LLaMA: Open and Efficient Foundation Language Models27 Feb

Other references · 27

  1. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,399
  2. 2019Unsupervised Cross-lingual Representation Learning at Scalecited by 3,935
  3. 2022Scaling Instruction-Finetuned Language Modelscited by 3,024
  4. 2022Self-Instruct: Aligning Language Models with Self-Generated Instructionscited by 2,724
  5. 2022BLOOM: A 176B-Parameter Open-Access Multilingual Language Modelcited by 1,984
  6. 2020mT5: A massively multilingual pre-trained text-to-text transformercited by 1,818
  7. 2023Pythia: A Suite for Analyzing Large Language Models Across Training and Scalingcited by 1,786
  8. 2018XNLI: Evaluating Cross-lingual Sentence Representationscited by 915
  9. 2020The State and Fate of Linguistic Diversity and Inclusion in the NLP Worldcited by 798
  10. 2019On the Cross-lingual Transferability of Monolingual Representationscited by 578
  11. 2018Massively Multilingual Sentence Embeddings for Zero-Shot Cross-Lingual Transfer and Beyondcited by 434
  12. 2016A Corpus and Evaluation Framework for Deeper Understanding of Commonsense Storiescited by 417
15 more
  1. 2020XCOPA: A Multilingual Dataset for Causal Commonsense Reasoningcited by 333
  2. 2023MEGA: Multilingual Evaluation of Generative AIcited by 293
  3. 2021MasakhaNER: Named Entity Recognition for African Languagescited by 155
  4. 2019Choosing Transfer Languages for Cross-Lingual Learningcited by 144
  5. 2021It's All in the Heads: Using Attention Heads as a Baseline for Cross-Lingual Transfer in Commonsense Reasoningcited by 69
  6. 2022NusaX: Multilingual Parallel Sentiment Dataset for 10 Indonesian Local Languagescited by 68
  7. 2020Zero-Shot Cross-Lingual Transfer with Meta Learningcited by 66
  8. 2018Modeling Language Variation and Universals: A Survey on Typological Linguistics for Natural Language Processingcited by 63
  9. 2019Code-Switched Language Models Using Neural Based Synthetic Data from Parallel Sentencescited by 55
  10. 2020Predicting Performance for Natural Language Processing Taskscited by 49
  11. 2021From Machine Translation to Code-Switching: Generating High-Quality Code-Switched Textcited by 29
  12. 2021Improving Zero-Shot Cross-Lingual Transfer Learning via Robust Trainingcited by 21
  13. 2022EntityCS: Improving Zero-Shot Cross-lingual Transfer with Entity-Centric Code Switchingcited by 8
  14. 2020Precise Task Formalization Matters in Winograd Schema Evaluationscited by 7
  15. 2022"Diversity and Uncertainty in Moderation" are the Key to Data Selection for Multilingual Few-shot Transfercited by 5

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2023: 18; 2024: 24; 2025: 7; 2026: 2.

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  4. 2024From LLMs to LLM-based Agents for Software Engineering: A Survey of Current, Challenges and Futurecited by 86
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  10. 2025Crosslingual Reasoning through Test-Time Scalingcited by 46
  11. 2025On the generalization of language models from in-context learning and finetuning: a controlled studycited by 40
  12. 2023When does In-context Learning Fall Short and Why? A Study on Specification-Heavy Taskscited by 37
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  2. 2023COPAL-ID: Indonesian Language Reasoning with Local Culture and Nuancescited by 35
  3. 2023Large Language Models as Annotators: Enhancing Generalization of NLP Models at Minimal Costcited by 33
  4. 2023DialogBench: Evaluating LLMs as Human-like Dialogue Systemscited by 31
  5. 2024Leveraging LLM-Respondents for Item Evaluation: a Psychometric Analysiscited by 31
  6. 2024Data Augmentation using Large Language Models: Data Perspectives, Learning Paradigms and Challengescited by 30
  7. 2024DataGen: Unified Synthetic Dataset Generation via Large Language Modelscited by 23
  8. 2023APoLLo: Unified Adapter and Prompt Learning for Vision Language Modelscited by 19
  9. 2024Retrieval-Augmented Data Augmentation for Low-Resource Domain Taskscited by 12
  10. 2024Leveraging ChatGPT in Pharmacovigilance Event Extraction: An Empirical Studycited by 12
  11. 2024SUTRA: Scalable Multilingual Language Model Architecturecited by 11
  12. 2024Unsupervised Distractor Generation via Large Language Model Distilling and Counterfactual Contrastive Decodingcited by 11
  13. 2024Delving into the Reversal Curse: How Far Can Large Language Models Generalize?cited by 11
  14. 2023Controllable Data Augmentation for Few-Shot Text Mining with Chain-of-Thought Attribute Manipulationcited by 9
  15. 2024A Review of Multimodal Explainable Artificial Intelligence: Past, Present and Futurecited by 9
  16. 2023CloudEval-YAML: A Practical Benchmark for Cloud Configuration Generationcited by 8
  17. 2024LlamaDuo: LLMOps Pipeline for Seamless Migration from Service LLMs to Small-Scale Local LLMscited by 8
  18. 2023From Big to Small Without Losing It All: Text Augmentation with ChatGPT for Efficient Sentiment Analysiscited by 6
  19. 2023Large Scale Foundation Models for Intelligent Manufacturing Applications: A Surveycited by 6
  20. 2023The Costly Dilemma: Generalization, Evaluation and Cost-Optimal Deployment of Large Language Modelscited by 5
  21. 2024HateCOT: An Explanation-Enhanced Dataset for Generalizable Offensive Speech Detection via Large Language Modelscited by 5
  22. 2023A Unified Framework for Generative Data Augmentation: A Comprehensive Surveycited by 4
  23. 2026AnomalyVFM -- Transforming Vision Foundation Models into Zero-Shot Anomaly Detectorscited by 4
  24. 2025Bridging Generative and Discriminative Learning: Few-Shot Relation Extraction via Two-Stage Knowledge-Guided Pre-trainingcited by 3
  25. 2023A ML-LLM pairing for better code comment classificationcited by 2
  26. 2024FormulaReasoning: A Dataset for Formula-Based Numerical Reasoningcited by 2
  27. 2023ChatGPT-guided Semantics for Zero-shot Learningcited by 1
  28. 2023Integrating curation into scientific publishing to train AI modelscited by 1
  29. 2024Speak & Spell: LLM-Driven Controllable Phonetic Error Augmentation for Robust Dialogue State Trackingcited by 1
  30. 2024Extended Japanese Commonsense Morality Dataset with Masked Token and Label Enhancementcited by 1
  31. 2026ReTabSyn: Realistic Tabular Data Synthesis via Reinforcement Learningcited by 1
  32. 2024CVE-LLM : Automatic vulnerability evaluation in medical device industry using large language modelscited by 0
  33. 2024Guidance-Based Prompt Data Augmentation in Specialized Domains for Named Entity Recognitioncited by 0
  34. 2024On the Necessity of World Knowledge for Mitigating Missing Labels in Extreme Classificationcited by 0
  35. 2024A Persuasion-Based Prompt Learning Approach to Improve Smishing Detection through Data Augmentationcited by 0
  36. 2025Facts Do Care About Your Language: Assessing Answer Quality of Multilingual LLMscited by 0
  37. 2025PromptAug: Fine-grained Conflict Classification Using Data Augmentationcited by 0
  38. 2025StaAgent: An Agentic Framework for Testing Static Analyzerscited by 0

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  5. 2022Bootstrapping Multilingual Semantic Parsers using Large Language Models
  6. 2024LLMs Beyond English: Scaling the Multilingual Capability of LLMs with Cross-Lingual Feedback
  7. 2025MMLU-ProX: A Multilingual Benchmark for Advanced Large Language Model Evaluation
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