JamPatoisNLI：牙买加土语自然语言推理数据集
JamPatoisNLI: A Jamaican Patois Natural Language Inference Dataset
摘要：
JamPatoisNLI提供了第一个用于克里奥尔语（Jamaican Patois）中的自然语言推理的数据集。许多使用最多的低资源语言是克里奥尔语。这些语言通常都有一个来自世界主要语言的词汇和一个独特的语法，反映了最初使用者的语言和通过克理奥尔化产生语言的过程。这使他们在探索从大型单语或多语言预训练模型迁移的有效性方面具有独特的地位。虽然我们的工作以及以前的工作表明，从这些模型转移到与其训练集中的语言无关的低资源语言并不是很有效，但我们希望从转移到克里奥尔语中得到更强的结果。事实上，我们的实验表明，JamPatoisNLI的少样本学习比这些无关语言的学习效果要好得多，并帮助我们开始了解克里奥尔语与其高资源基础语言之间的独特关系如何影响跨语言迁移。JamPatoisNLI由自然发生的前提和专家撰写的假设组成，是将研究转向传统上服务不足的语言的一步，也是理解跨语言NLP的有用基准。
英文摘要：
JamPatoisNLI provides the first dataset for natural language inference in a creole language, Jamaican Patois. Many of the most-spoken low-resource languages are creoles. These languages commonly have a lexicon derived from a major world language and a distinctive grammar reflecting the languages of the original speakers and the process of language birth by creolization. This gives them a distinctive place in exploring the effectiveness of transfer from large monolingual or multilingual pretrained models. While our work, along with previous work, shows that transfer from these models to low-resource languages that are unrelated to languages in their training set is not very effective, we would expect stronger results from transfer to creoles. Indeed, our experiments show considerably better results from few-shot learning of JamPatoisNLI than for such unrelated languages, and help us begin to understand how the unique relationship between creoles and their high-resource base languages affect cross-lingual transfer. JamPatoisNLI, which consists of naturally-occurring premises and expert-written hypotheses, is a step towards steering research into a traditionally underserved language and a useful benchmark for understanding cross-lingual NLP.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
