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Cross-Lingual Information Retrieval

Cross-Lingual Information Retrieval (CLIR) is a retrieval task in which search queries and candidate documents are written in different languages. CLIR can be very useful in some scenarios. For example, a reporter may want to search foreign language news to obtain different perspectives for her story; an inventor may explore the patents in another country to understand prior art.

Papers

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Showing 51–68 of 68 papers

TitleStatusHype
MT Quality Estimation: The CMU System for WMT’13—0
Multilingual Open QA on the MIA Shared Task—0
Multilingual Representation Distillation with Contrastive Learning—0
Multilingual Test Sets for Machine Translation of Search Queries for Cross-Lingual Information Retrieval in the Medical Domain—0
QueryBuilder: Human-in-the-Loop Query Development for Information Retrieval—0
Robust Document Representations for Cross-Lingual Information Retrieval in Low-Resource Settings—0
CLIReval: Evaluating Machine Translation as a Cross-Lingual Information Retrieval TaskCode0
Harnessing Cross-lingual Features to Improve Cognate Detection for Low-resource LanguagesCode0
Unsupervised Cross-Lingual Information Retrieval using Monolingual Data OnlyCode0
Cognition-aware Cognate DetectionCode0
Augmenting Passage Representations with Query Generation for Enhanced Cross-Lingual Dense RetrievalCode0
Macro-Average: Rare Types Are Important TooCode0
Cross-Dialect Information Retrieval: Information Access in Low-Resource and High-Variance LanguagesCode0
MuSeCLIR: A Multiple Senses and Cross-lingual Information Retrieval DatasetCode0
Cross-lingual Information Retrieval with BERTCode0
NeuralMind-UNICAMP at 2022 TREC NeuCLIR: Large Boring Rerankers for Cross-lingual RetrievalCode0
Cross-Lingual Low-Resource Set-to-Description Retrieval for Global E-CommerceCode0
A Resource-Light Method for Cross-Lingual Semantic Textual SimilarityCode0
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