mlsanityData to 7 Oct 2026

Cross-Lingual Retrieval Augmented Prompt for Low-Resource Languages

arXiv 2212.09651 ↗First posted 19 Dec 2022cs.CLcited by 17

On the map: Retrieval-augmented generation → Generation and context integration

Abstract (arXiv)

Multilingual Pretrained Language Models (MPLMs) have shown their strong multilinguality in recent empirical cross-lingual transfer studies. In this paper, we propose the Prompts Augmented by Retrieval Crosslingually (PARC) pipeline to improve the zero-shot performance on low-resource languages (LRLs) by augmenting the context with semantically similar sentences retrieved from a high-resource language (HRL) as prompts. PARC improves the zero-shot performance on three downstream tasks (binary sentiment classification, topic categorization and natural language inference) with multilingual parallel test sets across 10 LRLs covering 6 language families in both unlabeled settings (+5.1%) and labeled settings (+16.3%). PARC-labeled also outperforms the finetuning baseline by 3.7%. We find a significant positive correlation between cross-lingual transfer performance on one side, and the similarity between the high- and low-resource languages as well as the amount of low-resource pretraining data on the other side. A robustness analysis suggests that PARC has the potential to achieve even stronger performance with more powerful MPLMs.

Key facts. Cited by 17 papers in the map (data through 7 Oct 2026). Placed in Generation and context integration, one of 15 directions in Retrieval-augmented generation. Builds on 38 of its 48 references that are in the map. First posted on arXiv 19 Dec 2022.

Builds on

38 of 48 references.

Closest ancestors · 1

Same direction, newest first

  1. 2022Novelty Controlled Paraphrase Generation with Retrieval Augmented Conditional Prompt Tuning1 Feb

Other references · 37

  1. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,204
  2. 2020Language Models are Few-Shot Learnerscited by 32,199
  3. 2019Sentence-BERT: Sentence Embeddings using Siamese BERT-Networkscited by 9,049
  4. 2019BERTScore: Evaluating Text Generation with BERTcited by 5,462
  5. 2019DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lightercited by 4,243
  6. 2019Unsupervised Cross-lingual Representation Learning at Scalecited by 3,907
  7. 2020Dense Passage Retrieval for Open-Domain Question Answeringcited by 3,779
  8. 2017A Broad-Coverage Challenge Corpus for Sentence Understanding through Inferencecited by 2,665
  9. 2015Character-level Convolutional Networks for Text Classificationcited by 2,293
  10. 2020mT5: A massively multilingual pre-trained text-to-text transformercited by 1,813
  11. 2020Making Pre-trained Language Models Better Few-shot Learnerscited by 1,255
  12. 2021What Makes Good In-Context Examples for GPT-3?cited by 1,184
25 more
  1. 2020Multilingual Denoising Pre-training for Neural Machine Translationcited by 1,028
  2. 2020Exploiting Cloze Questions for Few Shot Text Classification and Natural Language Inferencecited by 934
  3. 2018XNLI: Evaluating Cross-lingual Sentence Representationscited by 913
  4. 2017Reading Wikipedia to Answer Open-Domain Questionscited by 777
  5. 2020XTREME: A Massively Multilingual Multi-task Benchmark for Evaluating Cross-lingual Generalizationcited by 738
  6. 2020Language-agnostic BERT Sentence Embeddingcited by 621
  7. 2020Making Monolingual Sentence Embeddings Multilingual using Knowledge Distillationcited by 591
  8. 2018Massively Multilingual Sentence Embeddings for Zero-Shot Cross-Lingual Transfer and Beyondcited by 434
  9. 2017Supervised Learning of Universal Sentence Representations from Natural Language Inference Datacited by 428
  10. 2020RocketQA: An Optimized Training Approach to Dense Passage Retrieval for Open-Domain Question Answeringcited by 410
  11. 2019On Measuring Social Biases in Sentence Encoderscited by 397
  12. 2021Do Prompt-Based Models Really Understand the Meaning of their Prompts?cited by 324
  13. 2020InfoXLM: An Information-Theoretic Framework for Cross-Lingual Language Model Pre-Trainingcited by 237
  14. 2020Are All Languages Created Equal in Multilingual BERT?cited by 206
  15. 2020The Multilingual Amazon Reviews Corpuscited by 142
  16. 2022mGPT: Few-Shot Learners Go Multilingualcited by 141
  17. 2021Language Models are Few-shot Multilingual Learnerscited by 92
  18. 2022Training Data is More Valuable than You Think: A Simple and Effective Method by Retrieving from Training Datacited by 61
  19. 2021Discrete and Soft Prompting for Multilingual Modelscited by 49
  20. 2017Learning Language Representations for Typology Predictioncited by 40
  21. 2020From Zero to Hero: On the Limitations of Zero-Shot Cross-Lingual Transfer with Multilingual Transformerscited by 35
  22. 2020Probing Multilingual BERT for Genetic and Typological Signalscited by 26
  23. 2022Zero-shot Cross-lingual Transfer of Prompt-based Tuning with a Unified Multilingual Promptcited by 25
  24. 2022Semantic-Oriented Unlabeled Priming for Large-Scale Language Modelscited by 12
  25. 2022MulZDG: Multilingual Code-Switching Framework for Zero-shot Dialogue Generationcited by 7

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2023: 6; 2024: 7; 2025: 2; 2026: 2.

17 papers.

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  1. 2024Retrieval-Augmented Generation for AI-Generated Content: A Surveycited by 352
  2. 2024Reliable, Adaptable, and Attributable Language Models with Retrievalcited by 73
  3. 2023Dr.ICL: Demonstration-Retrieved In-context Learningcited by 71
  4. 2024In-context Learning with Retrieved Demonstrations for Language Models: A Surveycited by 69
  5. 2023From Classification to Generation: Insights into Crosslingual Retrieval Augmented ICLcited by 17
  6. 2025On the Consistency of Multilingual Context Utilization in Retrieval-Augmented Generationcited by 10
  7. 2025Rescuing the Unpoisoned: Efficient Defense against Knowledge Corruption Attacks on RAG Systemscited by 9
  8. 2023Is Prompt-Based Finetuning Always Better than Vanilla Finetuning? Insights from Cross-Lingual Language Understandingcited by 7
  9. 2024MICAS: Multi-grained In-Context Adaptive Sampling for 3D Point Cloud Processingcited by 5
  10. 2026DaPT: A Dual-Path Framework for Multilingual Multi-hop Question Answeringcited by 3
  11. 2023XNLI 2.0: Improving XNLI dataset and performance on Cross Lingual Understanding (XLU)cited by 2
  12. 2023Cross-Lingual Constituency Parsing for Middle High German: A Delexicalized Approachcited by 2
5 more
  1. 2023Unleashing the Multilingual Encoder Potential: Boosting Zero-Shot Performance via Probability Calibrationcited by 2
  2. 2024Vector Retrieval with Similarity and Diversity: How Hard Is It?cited by 2
  3. 2024A Unified Data Augmentation Framework for Low-Resource Multi-Domain Dialogue Generationcited by 1
  4. 2024ChatZero:Zero-shot Cross-Lingual Dialogue Generation via Pseudo-Target Languagecited by 1
  5. 2026PromptPath: Prompt-Adaptive Computational Pathways for In-Context Learningcited by 0

Similar, not cited

Close in wording, no citation either way

  1. 2023Crosslingual Retrieval Augmented In-context Learning for Bangla
  2. 2025How and Where to Translate? The Impact of Translation Strategies in Cross-lingual LLM Prompting
  3. 2024Evaluating Zero-Shot Multilingual Aspect-Based Sentiment Analysis with Large Language Models
  4. 2023Multilingual LLMs are Better Cross-lingual In-context Learners with Alignment
  5. 2022kNN-Prompt: Nearest Neighbor Zero-Shot Inference
  6. 2026The Multilingual Curse at the Retrieval Layer: Evidence from Amharic
  7. 2025Compensating for Data with Reasoning: Low-Resource Machine Translation with LLMs
  8. 2024Cross-Lingual Transfer Robustness to Lower-Resource Languages on Adversarial Datasets