Abstract Machine translation (MT) is an important sub-field of natural language processing
that aims to translate natural languages using computers. In recent years, end-to-end neural …

Recently, the adversarial attack and defense technology has made remarkable
achievements and has been widely applied in the computer vision field, promoting its rapid …

With growing role of social media in shaping public opinions and beliefs across the world,
there has been an increased attention to identify and counter the problem of hate speech on …

Recently, generating adversarial examples has become an important means of measuring
robustness of a deep learning model. Adversarial examples help us identify the …

Recently, pre-trained language models have achieved remarkable success in a broad range
of natural language processing tasks. However, in multilingual setting, it is extremely …

Recent work in multilingual machine translation (MMT) has focused on the potential of
positive transfer between languages, particularly cases where higher-resourced languages …

Character-based representations in neural models have been claimed to be a tool to
overcome spelling variation in in word token-based input. We examine this claim in neural …

Featured Application This paper introduces factual relation information into Transformer-
based neural machine translation to improve translation quality. Abstract Transformer-based …

In historical linguistics, cognates are words that descend in direct line from a common
ancestor, called their proto-form, and therefore are representative of their respective …

Pre-trained language models, such as Bidirectional Encoder Representations from
Transformers (BERT), have demonstrated state-of-the-art performance in many Natural …