After more than 70 years of evolution, great achievements have been made in machine
translation. Especially in recent years, translation quality has been greatly improved with the …

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 …

Text retrieval is a long-standing research topic on information seeking, where a system is
required to return relevant information resources to user's queries in natural language. From …

In recent years, deep neural networks have been successful in both industry and academia,
especially for computer vision tasks. The great success of deep learning is mainly due to its …

Prompt tuning, in which a base pretrained model is adapted to each task via conditioning on
learned prompt vectors, has emerged as a promising approach for efficiently adapting large …

The recent emergence of Large Language Models based on the Transformer architecture
has enabled dramatic advancements in the field of Natural Language Processing. However …

Recommending cold items in recommendation systems is a longstanding challenge due to
the inherent differences between warm items, which are recommended based on user …

Non-autoregressive (NAR) generation, which is first proposed in neural machine translation
(NMT) to speed up inference, has attracted much attention in both machine learning and …

Abstract Knowledge distillation (KD) is the preliminary step for training non-autoregressive
translation (NAT) models, which eases the training of NAT models at the cost of losing …

Much recent effort has been invested in non-autoregressive neural machine translation,
which appears to be an efficient alternative to state-of-the-art autoregressive machine …