SEQUENCE-TO-SEQUENCE LEARNING FOR MOTION-AWARE CLAIM GENERATION

نویسندگان
چکیده

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Morphological Inflection Generation Using Character Sequence to Sequence Learning

Morphological inflection generation is the task of generating the inflected form of a given lemma corresponding to a particular linguistic transformation. We model the problem of inflection generation as a character sequence to sequence learning problem and present a variant of the neural encoder-decoder model for solving it. Our model is language independent and can be trained in both supervis...

متن کامل

Sequence to Sequence Learning for Event Prediction

This paper presents an approach to the task of predicting an event description from a preceding sentence in a text. Our approach explores sequence-to-sequence learning using a bidirectional multi-layer recurrent neural network. Our approach substantially outperforms previous work in terms of the BLEU score on two datasets derived from WIKIHOW and DESCRIPT respectively. Since the BLEU score is n...

متن کامل

Unsupervised Pretraining for Sequence to Sequence Learning

This work presents a general unsupervised learning method to improve the accuracy of sequence to sequence (seq2seq) models. In our method, the weights of the encoder and decoder of a seq2seq model are initialized with the pretrained weights of two language models and then fine-tuned with labeled data. We apply this method to challenging benchmarks in machine translation and abstractive summariz...

متن کامل

Convolutional Sequence to Sequence Learning

A. Weight Initialization We derive a weight initialization scheme tailored to the GLU activation function similar to Glorot & Bengio (2010); He et al. (2015b) by focusing on the variance of activations within the network for both forward and backward passes. We also detail how we modify the weight initialization for dropout. A.1. Forward Pass Assuming that the inputs x l of a convolutional laye...

متن کامل

Convolutional Sequence to Sequence Learning

The prevalent approach to sequence to sequence learning maps an input sequence to a variable length output sequence via recurrent neural networks. We introduce an architecture based entirely on convolutional neural networks.1 Compared to recurrent models, computations over all elements can be fully parallelized during training and optimization is easier since the number of non-linearities is fi...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

ژورنال

عنوان ژورنال: International Journal of Computing

سال: 2020

ISSN: 2312-5381,1727-6209

DOI: 10.47839/ijc.19.4.1997