Evaluating Large Language Models for Cross-Lingual Retrieval (2025.findings-emnlp)
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| Challenge: | Large Language Models (LLMs) have been evaluated as second-stage reranking models for monolingual IR, but a systematic comparison is lacking for cross-lingual reranked IR. |
| Approach: | They propose to use machine translation to evaluate rerankers in cross-lingual IR . they find that LLMs perform better than LLM-based reranked models . |
| Outcome: | The proposed model improves cross-lingual IR but relies on machine translation for the first stage. |
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