mlsanityData to 14 Oct 2026

XAMPLER: Learning to Retrieve Cross-Lingual In-Context Examples

arXiv 2405.05116 ↗First posted 8 May 2024cs.CLcited by 5

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Abstract (arXiv)

Recent studies indicate that leveraging off-the-shelf or fine-tuned retrievers, capable of retrieving relevant in-context examples tailored to the input query, enhances few-shot in-context learning of English. However, adapting these methods to other languages, especially low-resource ones, poses challenges due to the scarcity of cross-lingual retrievers and annotated data. Thus, we introduce XAMPLER: Cross-Lingual Example Retrieval, a method tailored to tackle the challenge of cross-lingual in-context learning using only annotated English data. XAMPLER first trains a retriever based on Glot500, a multilingual small language model, using positive and negative English examples constructed from the predictions of a multilingual large language model, i.e., MaLA500. Leveraging the cross-lingual capacity of the retriever, it can directly retrieve English examples as few-shot examples for in-context learning of target languages. Experiments on two multilingual text classification benchmarks, namely SIB200 with 176 languages and MasakhaNEWS with 16 languages, demonstrate that XAMPLER substantially improves the in-context learning performance across languages. Our code is available at https://github.com/cisnlp/XAMPLER.

Key facts. Cited by 5 papers in the map (data through 14 Oct 2026). Builds on 26 of its 35 references that are in the map. First posted on arXiv 8 May 2024.

Builds on

26 of 35 references.

References · 26

  1. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,399
  2. 2020Language Models are Few-Shot Learnerscited by 32,419
  3. 2023Llama 2: Open Foundation and Fine-Tuned Chat Modelscited by 13,028
  4. 2019Sentence-BERT: Sentence Embeddings using Siamese BERT-Networkscited by 9,170
  5. 2021Calibrate Before Use: Improving Few-Shot Performance of Language Modelscited by 1,392
  6. 2022No Language Left Behind: Scaling Human-Centered Machine Translationcited by 1,312
  7. 2020Making Pre-trained Language Models Better Few-shot Learnerscited by 1,256
  8. 2021What Makes Good In-Context Examples for GPT-3?cited by 1,195
  9. 2020XTREME: A Massively Multilingual Multi-task Benchmark for Evaluating Cross-lingual Generalizationcited by 742
  10. 2021Learning To Retrieve Prompts for In-Context Learningcited by 648
  11. 2020Making Monolingual Sentence Embeddings Multilingual using Knowledge Distillationcited by 593
  12. 2022SGPT: GPT Sentence Embeddings for Semantic Searchcited by 204
14 more
  1. 2023SIB-200: A Simple, Inclusive, and Big Evaluation Dataset for Topic Classification in 200+ Languages and Dialectscited by 152
  2. 2019Choosing Transfer Languages for Cross-Lingual Learningcited by 144
  3. 2023Compositional Exemplars for In-context Learningcited by 144
  4. 2023Glot500: Scaling Multilingual Corpora and Language Models to 500 Languagescited by 116
  5. 2020Multilingual Alignment of Contextual Word Representationscited by 114
  6. 2021Language Models are Few-shot Multilingual Learnerscited by 92
  7. 2023UPRISE: Universal Prompt Retrieval for Improving Zero-Shot Evaluationcited by 75
  8. 2023Dr.ICL: Demonstration-Retrieved In-context Learningcited by 72
  9. 2023Multilingual LLMs are Better Cross-lingual In-context Learners with Alignmentcited by 71
  10. 2024In-context Learning with Retrieved Demonstrations for Language Models: A Surveycited by 70
  11. 2024LLMs Are Few-Shot In-Context Low-Resource Language Learnerscited by 68
  12. 2023OFA: A Framework of Initializing Unseen Subword Embeddings for Efficient Large-scale Multilingual Continued Pretrainingcited by 37
  13. 2022XRICL: Cross-lingual Retrieval-Augmented In-Context Learning for Cross-lingual Text-to-SQL Semantic Parsingcited by 33
  14. 2023NLNDE at SemEval-2023 Task 12: Adaptive Pretraining and Source Language Selection for Low-Resource Multilingual Sentiment Analysiscited by 10

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2024: 1; 2025: 3; 2026: 1.

5 papers.

  1. 2025Relic: Enhancing Reward Model Generalization for Low-Resource Indic Languages with Few-Shot Examplescited by 6
  2. 2025Enhancing Large Language Models with Neurosymbolic Reasoning for Multilingual Taskscited by 4
  3. 2025Gradual Code-Switching as Inference-Time Cross-Lingual Representational Alignment for LLMscited by 3
  4. 2024Multilingual LLMs Inherently Reward In-Language Time-Sensitive Semantic Alignment for Low-Resource Languagescited by 0
  5. 2026When English Isn't the Best Teacher: Source Language Effects in Cross-Lingual In-Context Learningcited by 0