[PDF] Top 20 On The Alignment Problem In Multi Head Attention Based Neural Machine Translation
Has 10000 "On The Alignment Problem In Multi Head Attention Based Neural Machine Translation" found on our website. Below are the top 20 most common "On The Alignment Problem In Multi Head Attention Based Neural Machine Translation".
On The Alignment Problem In Multi Head Attention Based Neural Machine Translation
... an alignment head to help extract alignments in scenarios such as dictionary-guided transla- ...the alignment- assisted systems can achieve competitive per- formance compared to strong transformer ... See full document
9
Interactive Attention for Neural Machine Translation
... conventional attention model is conducted on the representation of source sentence (fixed af- ter generated) only with reading operation (Bahdanau et ...past attention information, and lead to ... See full document
12
On the Word Alignment from Neural Machine Translation
... that attention may not capture word alignment for an NMT model with multiple attentional ...word alignment which are agnostic to specific NMT ...word alignment induced by prediction ...that ... See full document
11
Multi Way, Multilingual Neural Machine Translation with a Shared Attention Mechanism
... the attention-based encoder-decoder network, as the attention mecha- nism, or originally called the alignment function in (Bahdanau et ...pair-specific attention mechanism by ... See full document
10
A Multi Task Architecture on Relevance based Neural Query Translation
... a multi-task learning approach to train a Neural Machine Translation (NMT) model with a Relevance-based Auxiliary Task (RAT) for search query ...this problem with our ... See full document
6
Target Foresight Based Attention for Neural Machine Translation
... in neural machine translation, an attention model is used to identify the aligned source words for a target word target foresight word in order to select translation con- text, but it ... See full document
11
Neural Machine Translation with Supervised Attention
... An attention mechanism is designed to predict the alignment of a target word with respect to source words (Bahdanau et ...this alignment prediction without the information about the target word ... See full document
10
Effective Approaches to Attention based Neural Machine Translation
... global attention approach gives a significant boost of ...local attention model with predictive alignments (row local-p) proves to be even better, giving us a further improve- ment of ... See full document
10
Incorporating Global Visual Features into Attention based Neural Machine Translation
... introduce multi-modal, attention- based Neural Machine Translation (NMT) models which incorporate visual features into different parts of both the encoder and the ...lutional ... See full document
12
Combining Character and Word Information in Neural Machine Translation Using a Multi Level Attention
... On the other hand, there have been multiple efforts to build models operating purely at the character level (Ling et al., 2015a; Yang et al., 2016; Lee et al., 2017). But splitting this finely can increase potential ... See full document
10
CKY based Convolutional Attention for Neural Machine Translation
... an attention mechanism for NMT based on CNNs, which imitates the CKY al- ...Japanese translation task showed that the proposed attention gained ...proposed attention in terms of memory ... See full document
6
A Neural Attention Model for Abstractive Sentence Summarization
... of neural machine translation, we combine a neural language model with a con- textual input ...the attention-based encoder of Bahdanau et ...soft alignment over the input ... See full document
11
Towards Bidirectional Hierarchical Representations for Attention based Neural Machine Translation
... over-translation problem observed in the transla- tion ...shorter translation of an average of ...the problem of over-translation is also ... See full document
10
Neural Hidden Markov Model for Machine Translation
... comparing neural HMM and attention-based NMT, we shed light on the role of the attention ...an alignment- based model that has a recurrent bidirectional en- coder and a recurrent ... See full document
6
Domain Adaptation and Attention Based Unknown Word Replacement in Chinese to Japanese Neural Machine Translation
... We expect the domain adaptation method to disambiguate the meaning of a word according to its context. For example in Table 3, both of the Japanese words “ ” and “ ” mean “field” and “area” but their meanings depend on ... See full document
9
Incorporating Word Reordering Knowledge into Attention based Neural Machine Translation
... the attention mechanism. To remit the computing cost of the attention mecha- nism when dealing with long sentences, Lu- ong et ...structural alignment biases in- to the attention mechanism and ... See full document
11
A Multi Hop Attention for RNN based Neural Machine Translation
... RNN based source-to-target at- tention mechanism where the number of parame- ters increases by repeating the calculation of multi- head attention for a single-source encoder like ... See full document
8
Alignment Based Neural Machine Translation
... as alignment. While we use larger vocabularies compared to the attention-based system, we ob- serve incorrect translations of rare ...right translation. Another problem occurs in ... See full document
12
Neural Machine Translation with Recurrent Attention Modeling
... to neural ma- chine translation (NMT) that used a fixed vec- tor representation of the input (Sutskever et ...Although attention is an intu- itively appealing concept and has been proven in practice, ... See full document
5
Multi Granularity Self Attention for Neural Machine Translation
... the translation perfor- ...of Attention In order to evaluate whether the proposed model is able to capture phrase patterns or not, we visualize the attention layers in the encoder 2 ...pay ... See full document
11
Related subjects