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RTE

自然语言推断(Natural Language Inference,NLI),又称文本蕴含识别(Recognizing Textual Entailment,RTE),是一项经典的自然语言理解任务。给定前提句与假设句,该任务要求判断两者之间蕴含、矛盾、中立的推理关系。

这里列举了我们在NLI任务上工作的代码,包括:ESIM(复现),KAIN,MIMN等。

部分模型的论文如下:

ESIM( "Enhanced LSTM for Natural Language Inference" by Chen et al. in 2016):https://arxiv.org/pdf/1609.06038.pdf

KAIN("Knowledge Augmented Inference Network for Natural Language Inference" by Jiang et al. in 2018):https://link.springer.com/chapter/10.1007/978-981-13-3146-6_11 该工作被ccks 2018接收,使用Wordnet作为外部知识,用TransE将关系三元组转化为稠密连续的向量形式,加入模型。

MIMN("Multi-turn Inference Matching Network for Natural Language Inference"by Chun et al. in 2018):https://arxiv.org/pdf/1901.02222.pdf 该工作为NLPCC 2018 outstanding paper

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