LLaMA(Low-resource Language Model Adaptation)是一种基础的大型语言模型,由Meta AI开发和公开发布¹。它可以用于多种任务的微调,比如对话生成、问答、文本摘要等。微调LLaMA模型的一般步骤如下: 准备数据集。你需要有一个与你的目标任务相关的数据集,比如对话数据、问答数据等。数据集应该是一个文本文件,每一行是一...
listing all of theFirefox language packsorApertium language modulesfor each low resource language would be unhelpful, as would be including all of the tools available for Basque noted in theACL Wiki, which would mainly mean cataloguing tools through theIXA group, some of which are open source, ...
Systematic Inequalities in Language Technology Performance across the World's Languages 社区问答 我要提问 Q1 论文试图解决什么问题? Q2 这是否是一个新的问题? Q3 这篇文章要验证一个什么科学假设? Q4 有哪些相关研究?如何归类?谁是这一课题在领域内值得关注的研究员?
Enhancing Low-Resource Language NMT Models Through Constrained Sampling-Based Data Augmentation人工智能自然语言处理神经网络机器翻译低资源语言数据增强约束采样数据增强(DA)是自然语言处理中的一种流行技术,特别是在机器翻译中.它涉及从现有数据集创建额外的训练数据以提高模型性能.然而,现有的针对低资源语言的DA方法...
We f ind that althoughtransformer-based methods generally outper-form traditional models, the two classes ofapproach remain competitive with each other.1 IntroductionWord alignment is a valuable tool for extendingthe coverage of natural language processing (NLP)applications to low-resource languages ...
Basil Abraham, Danish Goel, Divya Siddarth, Kalika Bali, Manu Chopra, Monojit Choudhury, Pratik Joshi, Preethi Jyothi, Sunayana Sitaram, Vivek Seshadri Language Resources and Evaluation Conference (LREC)|May 2020 Published by European Language Resources Association ...
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...
Machine Translation (MT) for low-resource language has low-coverage issues due to Out-Of-Vocabulary (OOV) Words. In this research we propose a method using sublexical translation to achieve wide-coverage in Example-Based Machine Translation (EBMT) for English to Bangla language. For sublexical ...
However, there are two problems that should be addressed: (i) how to learn a mapping function that project two language embeddings into a shared space with an unsupervised way. (ii) how to hold the performance of the trained offensive speech identification model when implementing transfer ...
The ACM Transactions on Asian and Low-Resource Language Information Processing (TALLIP) publishes high quality original archival papers and technical notes in the areas of computation and processing of information in Asian languages, low-resource languages of Africa, Australasia, Oceania and the Americas...