Conditional text generation often requires lexical constraints, ie, which words should or
shouldn't be included in the output text. While the dominant recipe for conditional text …

Automatic machine translation is super efficient to produce translations yet their quality is not
guaranteed. This technique report introduces TranSmart, a practical human-machine …

Computer-aided translation (CAT), the use of software to assist a human translator in the
translation process, has been proven to be useful in enhancing the productivity of human …

Lexically constrained neural machine translation (NMT), which controls the generation of
NMT models with pre-specified constraints, is important in many practical scenarios. Due to …

Machine translation systems are expected to cope with various types of constraints in many
practical scenarios. While neural machine translation (NMT) has achieved strong …

Text style transfer techniques are gaining popularity in natural language processing
allowing paraphrasing text in the required form: from toxic to neural, from formal to informal …

Domain-specific neural machine translation (NMT) systems (eg, in educational applications)
are socially significant with the potential to help make information accessible to a diverse set …

This paper describes our work in the WMT 2021 Machine Translation using Terminologies
Shared Task. We participate in the shared translation terminologies task in English to …

We propose a structured extension to bidirectional-context conditional language generation,
or" infilling," inspired by Frame Semantic theory (Fillmore, 1976). Guidance is provided …

Improving neural machine translation (NMT) systems with prompting has achieved
significant progress in recent years. In this work, we focus on how to integrate multi …