Multi-modal keyphrase generation aims to produce a set of keyphrases tha...
Large language models (LLMs) possess a wealth of knowledge encoded in th...
One challenge in text-to-image (T2I) generation is the inadvertent refle...
Current Transformer-based natural language understanding (NLU) models he...
Recently, the text-to-table generation task has attracted increasing
att...
k-Nearest neighbor machine translation (kNN-MT) has attracted increasing...
In real-world systems, scaling has been critical for improving the
trans...
Multilingual vision-language (V L) pre-training has achieved remarkabl...
Keyphrase prediction aims to generate phrases (keyphrases) that highly
s...
Knowledge-aided dialogue response generation aims at augmenting chatbots...
Neural chat translation (NCT) aims to translate a cross-lingual chat bet...
Document-level relation extraction (RE) aims to extract the relations be...
Keyphrase generation aims to automatically generate short phrases summar...
Simile recognition involves two subtasks: simile sentence classification...
Most existing pre-trained language representation models (PLMs) are
sub-...
k-Nearest-Neighbor Machine Translation (kNN-MT) becomes an important res...
Grammatical Error Correction (GEC) aims to automatically detect and corr...
The goal of the cross-lingual summarization (CLS) is to convert a docume...
Most dominant neural machine translation (NMT) models are restricted to ...
Generative commonsense reasoning requires machines to generate sentences...
Dominant sentence ordering models can be classified into pairwise orderi...
Controllable text generation is an appealing but challenging task, which...
Neural Chat Translation (NCT) aims to translate conversational text betw...
A good translation should not only translate the original content
semant...
A well-known limitation in pretrain-finetune paradigm lies in its
inflex...
Due to the great potential in facilitating software development, code
ge...
In aspect-based sentiment analysis (ABSA), many neural models are equipp...
The task of graph-to-text generation aims at producing sentences that
pr...
Multimodal machine translation (MMT), which mainly focuses on enhancing
...
Multi-modal neural machine translation (NMT) aims to translate source
se...
Unsupervised style transfer aims to change the style of an input sentenc...
Simile recognition is to detect simile sentences and to extract simile
c...
Previous studies on the domain adaptation for neural machine translation...
Sentence ordering is to restore the original paragraph from a set of
sen...
Referring Expression Comprehension (REC) is an emerging research spot in...
We address the problem of video moment localization with natural languag...
Benefiting from the excellent ability of neural networks on learning sem...
In aspect-level sentiment classification (ASC), it is prevalent to equip...
It is intuitive that semantic representations can be useful for machine
...
In this study, we first investigate a novel capsule network with dynamic...
In this paper, we propose an additionsubtraction twin-gated recurrent ne...
Although neural machine translation(NMT) yields promising translation
pe...
A great proportion of sequence-to-sequence (Seq2Seq) models for Neural
M...
With parallelizable attention networks, the neural Transformer is very f...
The dominant neural machine translation (NMT) models apply unified
atten...
Partially inspired by successful applications of variational recurrent n...
Neural machine translation (NMT) heavily relies on an attention network ...
The vanilla attention-based neural machine translation has achieved prom...
In this paper, we propose a bidimensional attention based recursive
auto...
Models of neural machine translation are often from a discriminative fam...