代码已经实现了开源: ratishsp/data2text-entity-py论文地址: Data-to-text Generation with Entity Modeling欢迎随时私信或评论探讨~我会尽量做到秒回的。 导语:前面我们讲了一些基于VAE或者GAN的生成模型用以…
《Data-to-textGenerationwithEntityModeling》https://arxiv.org/abs/1906.03221 这篇文章主要是以entities为中心的网络结构用于data2text生成。创建entities的表示形式,并动态更新。在每个timestep上,使用层次结构的attention,以输入的数据和entitymemory为条件生成文本。 2. ...
Recent advances in data-to-text generation have led to the use of large-scale datasets and neural network models which are trained end-to-end, without explicitly modeling what to say and in what order. In this work, we present a neural network architecture which incorporates content selection ...
To implement this hierarchical attention, at each decoding step t, the model learns a first set of attention scores a_{i,t} over entities e_i and a second set of attention scores \beta_{i,j,t} over records r_{i,j} belonging to entity e_i The a_{i,t}scores are normalized to ...
In the text generation stage, the coverage mechanism is added to remove the repeated words in the texts. In addition, in order to embed the positional association information in the data into the word vectors, we also add positional encoding to the word embedding. Then the word vectors are ...
Code for A Hierarchical Model for Data-to-Text Generation (Rebuffel, Soulier, Scoutheeten, Gallinari; ECIR 2020); most of this code is based on OpenNMT. UPDATE 11/03/2021: The original checkpoints used to produce results from the paper are officialy lost. However, I still have the actua...
Repository to track the progress in Natural Language Processing (NLP), including the datasets and the current state-of-the-art for the most common NLP tasks.
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Fact-based Data-to-Text Generation The Data2Text project aims to develop automated high-fidelity data-to-text generation technologies to address the shortcomings of template-based and the neural network-based approaches. Opens in a new tab