It was renamed to reflect that endangerment is a loaded term that both may not reflect the views of language communities speaking minority languages. low-resource-languages focuses this list on a lack of digital resources compared to other, high resourced languages.Tools which are built for these...
resource languages have significantly lower attack success rate, which suggests that the cross-lingual vulnerability mainly applies to low-resource languages. Previously, limited training on low-resource languages primarily affects speakers of those languages, causing technological disparities. However, our ...
Language models struggle in generating correct code for low resource programming languages, since these are underrepresented in training data. Popular approaches use either examples or documentation to improve the performance of these models. Instead of considering the independent retr...
Recently, very large language models (LLMs) have shown exceptional performance on several English NLP tasks with just in-context learning (ICL), but their utility in other languages is still underexplored. We investigate their effectiveness for NLP tasks in low-resource languages (LRLs), especially...
Low-resource languages1 often have limited labeled data or even without any labels, which may make us disable to train a robust and accurate offensive speech identification model. To build an offensive speech identification model for low-resource languages, recently many researchers used cross-lingual...
当当中国进口图书旗舰店在线销售正版《预订 Machine Translation and Transliteration involving Related, Low-resource Languages 涉及相关低资源语言的机器翻译与》。最新《预订 Machine Translation and Transliteration involving Related, Low-resource Languages 涉及
Crowdsourcing Speech Data for Low-Resource Languages from Low-Income Workers Basil Abraham, Danish Goel, Divya Siddarth, Kalika Bali, Manu Chopra, Monojit Choudhury, Pratik Joshi, Preethi Jyothi, Sunayana Sitaram, Vivek Seshadri Language Resources and Evaluation Conferenc...
For low-resource languages, keyword search (KWS) remains challenging due to the lack of training data. This work aims to bolster KWS performance in low-resource languages by incorporating word burst information into the decision process. We find that this information can improve performance when we...
The scarcity of parallel datasets for low-resource languages can hinder MT development. To address this, gaHealth was developed, the first bilingual corpus of health data for the Irish language. Focusing on the health domain, models developed using this in-domain dataset exhibited very significant ...
Language models struggle in generating correct code for low resource programming languages, since these are underrepresented in training data. Popular approaches use either examples or documentation to improve the performance of these models. Instead of considering the indep...