Multilingual Retrieval-Augmented Generation for Knowledge-Intensive Question Answering Task (2026.findings-eacl)
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| Challenge: | Existing studies focus on English as the data language for RAG, resulting in limited coverage of multilingual RAG. |
| Approach: | They propose a method that translates retrieved documents into a common language before generating the response. |
| Outcome: | The proposed approach improves efficiency on knowledge-intensive tasks but introduces inconsistencies due to cross-lingual variations in the retrieved content. |
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