Large language models (LLMs) such as ChatGPT can produce coherent, cohesive, relevant,
and fluent answers for various natural language processing (NLP) tasks. Taking document …

Neural Machine Translation (NMT) can be improved by including document-level contextual
information. For this purpose, we propose a hierarchical attention model to capture the …

Existing neural machine translation (NMT) models generally translate sentences in isolation,
missing the opportunity to take advantage of document-level information. In this work, we …

Zero pronouns (ZPs) are frequently omitted in pro-drop languages (eg Chinese, Hungarian,
and Hindi), but should be recalled in non-pro-drop languages (eg English). This …

This paper does not aim at introducing a novel model for document-level neural machine
translation. Instead, we head back to the original Transformer model and hope to answer the …

This paper investigates the ability of multilingual BERT (mBERT) language model to transfer
syntactic knowledge cross-lingually, verifying if and to which extent syntactic dependency …

Recent years have seen a surge of interest in dialogue translation, which is a significant
application task for machine translation (MT) technology. However, this has so far not been …

A typical end-to-end task-oriented dialog system transfers context into dialog state, and upon
which generates a response, which usually faces the problem of error propagation from both …

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

This paper describes the Tencent AI Lab's submission of the WMT 2020 shared task on chat
translation in English-German. Our neural machine translation (NMT) systems are built on …