Multimodal machine translation (MMT) aims to improve neural machine translation (NMT)
with additional visual information, but most existing MMT methods require paired input of …

Text image translation (TIT) aims to translate the source texts embedded in the image to
target translations, which has a wide range of applications and thus has important research …

Multi-modal neural machine translation (MNMT) aims to translate sentences from the source
language into the target language with the aid of corresponding images. Unfortunately, there …

In recent years, multi-modal machine translation has attracted significant interest in both
academia and industry due to its superior performance. It takes both textual and visual …

With the continuous advancement of deep learning technology, pretrained language models
have emerged as crucial tools for natural language processing tasks. However, optimization …

Abstract Nowadays, Machine Learning is one of the most dynamic fields, as it attracts strong
research interest from both industry and academia alike. It is not surprising that a huge …

The semantic relations between language and vision modalities become more and more
vital since they can effectively facilitate downstream multi-modal tasks. Although several …

构建一个回复多样性的开放型对话系统模型, 以尝试解决对话系统在回复过程中回答单调的问题
. 提出一种融合双向长短期记忆神经网络和强化学习模型的生成式对话方法. 首先 …

Multi-modal machine translation (MMT) aims at exploring better translation systems by
integrating the visual annotation which presents the content described in the bilingual …

Multi-modal neural machine translation (MNMT) aims to integrate visual and textual
information to translate source sentences into target and attracts a lot of attentions. Existing …