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Learned Sparse Retrievers (LSR) have evolved into an effective retrieval strategy that can bridge the gap between traditional keyword-based sparse retrievers and embedding-based dense retrievers. At its core, learned sparse retrievers try to learn th
Externí odkaz:
http://arxiv.org/abs/2408.11119
Machine Translation (MT) between linguistically dissimilar languages is challenging, especially due to the scarcity of parallel corpora. Prior works suggest that pivoting through a high-resource language can help translation into a related low-resour
Externí odkaz:
http://arxiv.org/abs/2406.13332
In this paper, we explore the utility of Translationese as synthetic data created using machine translation for pre-training language models (LMs). Pre-training requires vast amounts of monolingual data, which is mostly unavailable for languages othe
Externí odkaz:
http://arxiv.org/abs/2403.13638
Akademický článek
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Autor:
Brahmbhatt KJ; Medicine, Government Medical College, Baroda, Vadodara, IND., Doshi MJ; Medicine, Government Medical College, Baroda, Vadodara, IND., Dave M; Medicine, Government Medical College, Baroda, Vadodara, IND., Contractor H; Medicine, Government Medical College, Baroda, Vadodara, IND., Shah K; Medicine, Government Medical College, Baroda, Vadodara, IND.
Publikováno v:
Cureus [Cureus] 2024 Jul 21; Vol. 16 (7), pp. e65057. Date of Electronic Publication: 2024 Jul 21 (Print Publication: 2024).