Simple Yet Effective Neural Ranking and Reranking Baselines for Cross-Lingual Information Retrieval

By Jimmy Lin et al

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Table of Contents

1. Introduction
2. Mono-lingual Retrieval Overview
3. Cross-Lingual Retrieval Methods

Summary

The document discusses the challenges and advancements in cross-lingual information retrieval. It provides a conceptual framework for organizing different approaches to cross-lingual retrieval and offers reproducible baselines for the TREC 2022 NeuCLIR test collection. The work focuses on the relationship between different retrieval methods and the design choices for efficient cross-lingual retrieval. The authors propose document translation, query translation, and the use of language-independent representations as possible designs for first-stage retrieval in cross-lingual settings. The paper also introduces cross-encoders for reranking and discusses fusion techniques. Overall, the work aims to provide a solid foundation for future research in cross-lingual information retrieval.