Knowledge base question answering (KBQA) aims to answer a question over a knowledge
base (KB). Early studies mainly focused on answering simple questions over KBs and …

Large pre-trained language models (LMs) have demonstrated the ability to obtain good
performance on downstream tasks with limited examples in cross-lingual settings. However …

Generating artistic portraits from face photos presents a complex challenge that requires
high-quality image synthesis and a deep understanding of artistic style and facial features …

This paper presents a survey on multilingual Knowledge Graph Question Answering
(mKGQA). We employ a systematic review methodology to collect and analyze the research …

Providing access to information is the main and most important purpose of the Web.
However, despite available easy-to-use tools (eg, search engines, chatbots, question …

Abstract Cross-lingual Machine Reading Comprehension (xMRC) is a challenging task due
to the lack of training data in low-resource languages. Recent approaches use training data …

This research paper proposes an approach called Lingua Franca that improves machine
translation quality by utilizing information from a knowledge graph to translate named …

Our research focuses on the most prevalent type of queries—simple questions—exemplified
by questions like “What is the capital of France?”. These questions reference an entity such …

With the rapid development of wireless networks, the scale of network devices is constantly
expanding. Experts spend vast amounts of time consulting and dealing with various network …

In this paper, we present DuReader_retrieval, a large-scale Chinese dataset for passage
retrieval. DuReader_retrieval contains more than 90K queries and over 8M unique …