mlsanityData to 7 Oct 2026

SandboxAQ's submission to MRL 2024 Shared Task on Multi-lingual Multi-task Information Retrieval

arXiv 2410.21501 ↗First posted 28 Oct 2024cs.CLcited by 0

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Abstract (arXiv)

This paper explores the problems of Question Answering (QA) and Named Entity Recognition (NER) in five diverse languages. We tested five Large Language Models with various prompting methods, including zero-shot, chain-of-thought reasoning, and translation techniques. Our results show that while some models consistently outperform others, their effectiveness varies significantly across tasks and languages. We saw that advanced prompting techniques generally improved QA performance but had mixed results for NER; and we observed that language difficulty patterns differed between tasks. Our findings highlight the need for task-specific approaches in multilingual NLP and suggest that current models may develop different linguistic competencies for different tasks.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 37 of its 56 references that are in the map. First posted on arXiv 28 Oct 2024.

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37 of 56 references.

References · 37

  1. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,204
  2. 2023GPT-4 Technical Reportcited by 18,132
  3. 2019Unsupervised Cross-lingual Representation Learning at Scalecited by 3,907
  4. 2024Gemma 2: Improving Open Language Models at a Practical Sizecited by 1,928
  5. 2023DSPy: Compiling Declarative Language Model Calls into Self-Improving Pipelinescited by 803
  6. 2020XTREME: A Massively Multilingual Multi-task Benchmark for Evaluating Cross-lingual Generalizationcited by 738
  7. 2019On the Cross-lingual Transferability of Monolingual Representationscited by 575
  8. 2020TyDi QA: A Benchmark for Information-Seeking Question Answering in Typologically Diverse Languagescited by 486
  9. 2019MLQA: Evaluating Cross-lingual Extractive Question Answeringcited by 339
  10. 2022Demonstrate-Search-Predict: Composing retrieval and language models for knowledge-intensive NLPcited by 316
  11. 2024Aya Model: An Instruction Finetuned Open-Access Multilingual Language Modelcited by 292
  12. 2023Not All Languages Are Created Equal in LLMs: Improving Multilingual Capability by Cross-Lingual-Thought Promptingcited by 163
25 more
  1. 2020MKQA: A Linguistically Diverse Benchmark for Multilingual Open Domain Question Answeringcited by 151
  2. 2024How do Large Language Models Handle Multilingualism?cited by 148
  3. 2020XOR QA: Cross-lingual Open-Retrieval Question Answeringcited by 121
  4. 2024Aya 23: Open Weight Releases to Further Multilingual Progresscited by 121
  5. 2024Understanding and Mitigating Language Confusion in LLMscited by 75
  6. 2024From LLM to NMT: Advancing Low-Resource Machine Translation with Claudecited by 57
  7. 2024Generate-then-Ground in Retrieval-Augmented Generation for Multi-hop Question Answeringcited by 51
  8. 2020Synthetic Data Augmentation for Zero-Shot Cross-Lingual Question Answeringcited by 41
  9. 2020Single-/Multi-Source Cross-Lingual NER via Teacher-Student Learning on Unlabeled Data in Target Languagecited by 37
  10. 2023Universal NER: A Gold-Standard Multilingual Named Entity Recognition Benchmarkcited by 26
  11. 2022QAmeleon: Multilingual QA with Only 5 Examplescited by 25
  12. 2020UniTrans: Unifying Model Transfer and Data Transfer for Cross-Lingual Named Entity Recognition with Unlabeled Datacited by 24
  13. 2024GPT-4 vs. Human Translators: A Comprehensive Evaluation of Translation Quality Across Languages, Domains, and Expertise Levelscited by 20
  14. 2020Towards Zero-Shot Multilingual Synthetic Question and Answer Generation for Cross-Lingual Reading Comprehensioncited by 17
  15. 2021Question Answering Survey: Directions, Challenges, Datasets, Evaluation Matricescited by 17
  16. 2023SemEval-2023 Task 2: Fine-grained Multilingual Named Entity Recognition (MultiCoNER 2)cited by 17
  17. 2023mCL-NER: Cross-Lingual Named Entity Recognition via Multi-view Contrastive Learningcited by 14
  18. 2024The Unreasonable Effectiveness of Eccentric Automatic Promptscited by 12
  19. 2023Enhancing Cross-lingual Transfer via Phonemic Transcription Integrationcited by 11
  20. 2023PAXQA: Generating Cross-lingual Question Answering Examples at Training Scalecited by 10
  21. 2022Language Agnostic Multilingual Information Retrieval with Contrastive Learningcited by 8
  22. 2023Bridging the Language Gap: Knowledge Injected Multilingual Question Answeringcited by 5
  23. 2024M2QA: Multi-domain Multilingual Question Answeringcited by 5
  24. 2023Promoting Generalized Cross-lingual Question Answering in Few-resource Scenarios via Self-knowledge Distillationcited by 1
  25. 2024Synergistic Approach for Simultaneous Optimization of Monolingual, Cross-lingual, and Multilingual Information Retrievalcited by 1

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  1. 2023DAMO-NLP at SemEval-2023 Task 2: A Unified Retrieval-augmented System for Multilingual Named Entity Recognition
  2. 2025How and Where to Translate? The Impact of Translation Strategies in Cross-lingual LLM Prompting
  3. 2025Agri-Query: A Case Study on RAG vs. Long-Context LLMs for Cross-Lingual Technical Question Answering
  4. 2025Multilingual Retrieval-Augmented Generation for Knowledge-Intensive Task
  5. 2021Investigating Post-pretraining Representation Alignment for Cross-Lingual Question Answering
  6. 2023Bridging the Language Gap: Dynamic Learning Strategies for Improving Multilingual Performance in LLMs
  7. 2023Cross-lingual QA: A Key to Unlocking In-context Cross-lingual Performance
  8. 2024NatLan: Native Language Prompting Facilitates Knowledge Elicitation Through Language Trigger Provision and Domain Trigger Retention