论文标题
应用一个通用序列到序列模型，以生成简单有效的键形生成
Applying a Generic Sequence-to-Sequence Model for Simple and Effective Keyphrase Generation
论文作者
论文摘要
近年来，提出了许多键形生成（KPG）方法，包括复杂的模型架构，专用的培训范式和解码策略。在这项工作中，我们选择简单性，并展示如何使用简单的训练过程轻松地将常用的SEQ2SEQ语言模型BART（BART）轻松适应以在单个批处理计算中生成键形。五个基准测试的经验结果表明，我们的方法与现有的最先进的jpg系统一样好，但使用了更简单，易于部署的框架。
In recent years, a number of keyphrase generation (KPG) approaches were proposed consisting of complex model architectures, dedicated training paradigms and decoding strategies. In this work, we opt for simplicity and show how a commonly used seq2seq language model, BART, can be easily adapted to generate keyphrases from the text in a single batch computation using a simple training procedure. Empirical results on five benchmarks show that our approach is as good as the existing state-of-the-art KPG systems, but using a much simpler and easy to deploy framework.
