首先,Interpreter接收自然语言问句作为输入,采用带GRU的双向RNN模型,输出一个对问句的表示并存储在短时记忆中。在每个 t 时刻针对每个词向量xt,会输出一个隐状态ht。最终问句表示的长度即为句子长度,在每个时刻 t 包括了隐状态向量h,词向量x以及词自身的信息。问句表示将作为Enquirer以及Answerer的输入。 Enquirer的工...
Neural Generative Question Answering笔记 来源: IJCAI 2016 原文MotivationQA knowledge based raw text 基于符号表示 基于深度学习 embedding/query-based generation-based问答可以看做单轮的对话系统。 最近的深度学习的发展增加了generation-based QA方法的可能性。
Question answeringNatural language ProcessNeural generative model in question answering (QA) usually employs sequence-to-sequence (Seq2Seq) learning to generate answers based on the user's questions as opposed to the retrieval-based model...
摘要: Neural generative model in question answering (QA) usually employs sequence-to-sequence (Seq2Seq) learning to generate answers based on the user's questions as opposed to the retrieval-based model...关键词: Multitask learning Generative model Question answering Natural language Process ...
RACE (ReAding Comprehension from Examinations)(Lai et al.,2017) is a question-answering dataset derived from reading comprehension exams conducted in middle and high school English lessons in China. Therefore, the context, questions, and answers were created by domain experts. However, it is worth...
Multitask learning for neural generative question answering Y Huang, T Zhong – Machine Vision and Applications, 2018 – Springer… Building chatbot in human–computer conversation via natural language is one of the most … zbMATHGoogle Scholar. 2. Bahdanau, D., Cho, K., Bengio, Y.: Neural ...
Large Neural networks, especially ones with transformer-based architectures, perform extremely well not only on Extractive Question Answering but also on Generative Question Answering(QA). But these models are computationally expensive and time-consuming. This makes them unusable in latency-sensitive applic...
分为两个步骤:Generative Model和Inference Network Generative Model 给定图像i,建立p(x,z,a| i)p(x,z,a| i)的模型,即关于问题、回答和program关系的模型。 模型分解为: p(x,z,a| i)=p(z)p(x| z)p(a| z,i)p(x,z,a| i)=p(z)p(x| z)p(a| z,i) 步骤:首先从program z的先验分布...
Machine comprehension by text-to-text neural question generation.2017 A unified auery-based generative model for question generation and question answering.2017 Neural question generation from text: A preliminary study.2017NLPcc 三、模型 gated self-attention: 1.计算self matching representation,来源于论文...
The unsupervised component is based on a generative model in which latent sentences generate the unpaired logical forms. We apply thi... KM Hermann,Tomávs Kovcisk,E Grefenstette,... 被引量: 698发表: 2015年 Overview of the TREC 2007 Question Answering Track The TREC 2007 question answering (...