https://bitbucket.org/gg42554/cl-sts
공식 코드A Resource-Light Method for Cross-Lingual Semantic Textual Similarity
Papers with Code 아카이브
Cross-Lingual Information Retrieval
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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.
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/LiuChang97/CLMN
공식 코드Cross-Lingual Low-Resource Set-to-Description Retrieval for Global E-Commerce
https://github.com/dipteshkanojia/challengeCognateFF
공식 코드Harnessing Cross-lingual Features to Improve Cognate Detection for Low-resource Languages
https://github.com/ielab/xqg4xdr
공식 코드Augmenting Passage Representations with Query Generation for Enhanced Cross-Lingual Dense Retrieval
https://github.com/khuangaf/concrete
공식 코드CONCRETE: Improving Cross-lingual Fact-checking with Cross-lingual Retrieval
https://github.com/mainlp/wikidir
공식 코드Cross-Dialect Information Retrieval: Information Access in Low-Resource and High-Variance Languages
https://github.com/prashantksharma/CaCD
공식 코드https://github.com/primeqa/primeqa
공식 코드https://github.com/rlitschk/UnsupCLIR
공식 코드Unsupervised Cross-Lingual Information Retrieval using Monolingual Data Only
https://github.com/thammegowda/007-mt-eval-macro
공식 코드https://github.com/unicamp-dl/neuclir22-mt5
공식 코드NeuralMind-UNICAMP at 2022 TREC NeuCLIR: Large Boring Rerankers for Cross-lingual Retrieval
https://github.com/MulukenW/test
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.