首先利用 Sentence-Bert 抽取出不同的 view 然后使用 BART,对 view 进行编码,传递给 decoder 进行摘要生成。 Conversation View Extraction if informative structures in the form of small blocks can be explicitly extracted from long conversations, models may be able to understand them better in a more orga...
to extract the output sequence from that vector. The second LSTM is essentially a recurrent neural network language model except that it is conditioned on the input sequence. (Note that this page refers to the original seq2seq not general sequence-to-sequence models) Introduced by Sutskever et ...
论文阅读 | Learning Neural Sequence-to-Sequence Models from Weak Feedback with Bipolar Ramp Loss https://arxiv.org/abs/1907.03748 已有研究工作: 已有的研究工作主要关注完全监督情况下的问题,如有对应文本的机器翻译,在弱监督领域研究较少,往往使用结构化的预测目标。 本文的创新点: 本文主要研究的是从弱反...
每次训练采样N个序列 在每次训练的时候,基于当前的模型采样得到N个完整的序列。采样基于Decoder每个时刻t的输出经softmax后的结果,并作为下一时刻的输入。原文中一开始说每次训练指采样一个序列,但是这对模型来说Variance非常大,因为不同的序列得到的Reward差别很大,模型的方差自然也很大。 通过ROUGE等方法得到reward并...
2014 - Sequence to Sequence models 2014 年,Sutskever 等人提出了 Seq2Seq 模型。Seq2Seq 模型属于编码器-解码器结构,在自然语言处理、计算机视觉、语音识别等领域都有非常广泛的应用 Learning Phrase Representations using RNN Encoder-Decoder for Statistical Machine Translation-2014 ...
Sequence-to-sequence models are a powerful workhorse of NLP. Most variants employ a softmax transformation in both their attention mechanism and output layer, leading to dense alignments and strictly positive output probabilities. This density is wasteful, making models less interpretable and assigning ...
Neural Sequence-to-Sequence models have proven to be accurate and robust for many sequence prediction tasks, and have become the standard approach for automatic translation of text. The models work in a five stage blackbox process that involves encoding a source sequence to a vector space and th...
几篇论文实现代码:《Sparse Sequence-to-Sequence Models》(ACL 2019) GitHub: http://t.cn/AiQID5Y1 《RANet: Ranking Attention Network for Fast Video Object Segmentation》(ICCV 2019) GitHub: http://t...
This tutorial introduces a new and powerful set of techniques variously called "neural machine translation" or "neural sequence-to-sequence models". These techniques have been used in a number of tasks regarding the handling of human language, and can be a powerful tool in the toolbox of anyon...
Lingvo is a Tensorflow framework offering a complete solution for collaborative deep learning research, with a particular focus towards sequence-to-sequence models. Lingvo models are composed of modular building blocks that are flexible and easily extensible, and experiment configurations are centralized an...