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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
Vernacular Search Query Translation with Unsupervised Domain Adaptation—0
Weakly Supervised Attentional Model for Low Resource Ad-hoc Cross-lingual Information Retrieval—0
What Set of Documents to Present to an Analyst?—0
Adaptation of Statistical Machine Translation Model for Cross-Lingual Information Retrieval in a Service Context—0
Zero-Shot Cross-Lingual Reranking with Large Language Models for Low-Resource Languages—0
A Multi-Task Architecture on Relevance-based Neural Query Translation—0
Anveshana: A New Benchmark Dataset for Cross-Lingual Information Retrieval On English Queries and Sanskrit Documents—0
A Probabilistic Translation Method for Dictionary-based Cross-lingual Information Retrieval in Agglutinative Languages—0
A Study of Neural Matching Models for Cross-lingual IR—0
A Supervised Model for Extraction of Multiword Expressions, Based on Statistical Context Features—0
AyutthayaAlpha: A Thai-Latin Script Transliteration Transformer—0
Backretrieval: An Image-Pivoted Evaluation Metric for Cross-Lingual Text Representations Without Parallel Corpora—0
Bag-of-Words Forced Decoding for Cross-Lingual Information Retrieval—0
Biomedical Chinese-English CLIR Using an Extended CMeSH Resource to Expand Queries—0
Building a Dataset of Multilingual Cognates for the Romanian Lexicon—0
cEnTam: Creation and Validation of a New English-Tamil Bilingual Corpus—0
Chinese Characters Mapping Table of Japanese, Traditional Chinese and Simplified Chinese—0
CLIRMatrix: A massively large collection of bilingual and multilingual datasets for Cross-Lingual Information Retrieval—0
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