WebJun 16, 2024 · Recent studies have demonstrated the cross-lingual alignment ability of multilingual pretrained language models. In this work, we found that the cross-lingual … Cross-language information retrieval (CLIR) is a subfield of information retrieval dealing with retrieving information written in a language different from the language of the user's query. The term "cross-language information retrieval" has many synonyms, of which the following are perhaps the most frequent: cross-lingual information retrieval, translingual information retrieval, multilingual information retrieval. The term "multilingual information retrieval" refers more genera…
[2204.08887] Cross-Lingual Phrase Retrieval - arXiv.org
WebGitHub - amiekong/cross-lingual-retrieval: Implementing an English-Spanish Cross-Lingual Information Retrieval System With Topic Model Query Expansion amiekong / cross-lingual-retrieval Public Star main 1 branch 0 tags Code 8 commits Failed to load latest commit information. static templates .gitignore Kong_Amie_Report.pdf Procfile … WebExtraction, Information Retrieval, Cross Lingual, Multilingual. I. INTRODUCTION Snippet is the most salient information in a document or in a retrieved documents (in case of search engine) and conveying it in short space, became an active field of research in both Information Retrieval (IR) and Natural Language Processing (NLP) communities. As per brussel sprouts with gochujang
Cross-Lingual Phrase Retrieval - ACL Anthology
WebApr 19, 2024 · Cross-lingual retrieval aims to retrieve relevant text across languages. Current methods typically achieve cross-lingual retrieval by learning language-agnostic text representations in word or sentence level. However, how to learn phrase representations for cross-lingual phrase retrieval is still an open problem. WebFeb 6, 2016 · Cross Lingual Information Retrieval provides a solution for that barrier which allows a user to ask a query in native language and then to get the document in different … WebJun 16, 2024 · Figure 3: Overview of Cross-lingual retrieval self-supervised training. 1:function Mine ( Θ, Di, Dj ) 2: Input: (1) monolingual data sets Di and Dj for language i and j respectively, (2) a pretrained model Θ , 3: Set k, M, τ. to be the desired KNN size, the desired mining size, and the desired minimum score threshold respectively. examples of genre conventions