Most Downloaded Articles

Open access

ISSN: 2666-6510

Graph neural networks: A review of methods and applications

Lots of learning tasks require dealing with graph data which contains rich relation information among elements. Modeling physics systems, learning molecular fingerprints, predicting protein interface,...

Share article

Pre-trained models: Past, present and future

Large-scale pre-trained models (PTMs) such as BERT and GPT have recently achieved great success and become a milestone in the field of artificial intelligence (AI). Owing to sophisticated pre-training...

Share article

Neural machine translation: A review of methods, resources, and tools

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 machine translation (NMT)...

Share article

Data augmentation approaches in natural language processing: A survey

As an effective strategy, data augmentation (DA) alleviates data scarcity scenarios where deep learning techniques may fail. It is widely applied in computer vision then introduced to natural language...

Share article

A survey on heterogeneous information network based recommender systems: Concepts, methods, applications and resources

As an important way to alleviate information overload, a recommender system aims to filter out irrelevant information for users and provides them items that they may be interested in. In recent years,...

Share article

Survey: Transformer based video-language pre-training

Inspired by the success of transformer-based pre-training methods on natural language tasks and further computer vision tasks, researchers have started to apply transformer to video processing. This...

Share article

Advances and challenges in conversational recommender systems: A survey

Recommender systems exploit interaction history to estimate user preference, having been heavily used in a wide range of industry applications. However, static recommendation models are difficult to...

Share article

A comprehensive survey of entity alignment for knowledge graphs

Knowledge Graphs (KGs), as a structured human knowledge, manage data in an ease-of-store, recognizable, and understandable way for machines and provide a rich knowledge base for different artificial...

Share article

Neural, symbolic and neural-symbolic reasoning on knowledge graphs

Knowledge graph reasoning is the fundamental component to support machine learning applications such as information extraction, information retrieval, and recommendation. Since knowledge graphs can...

Share article

Learning towards conversational AI: A survey

Recent years have witnessed a surge of interest in the field of open-domain dialogue. Thanks to the rapid development of social media, large dialogue corpus from the Internet builds up a fundamental...

Share article

Human motion modeling with deep learning: A survey

The aim of human motion modeling is to understand human behaviors and create reasonable human motion like real people given different priors. With the development of deep learning, researchers tend...

Share article

CPM: A large-scale generative Chinese Pre-trained language model

Pre-trained Language Models (PLMs) have proven to be beneficial for various downstream NLP tasks. Recently, GPT-3, with 175 billion parameters and 570 GB training data, drew a lot of attention due to...

Share article

Extracting Events and Their Relations from Texts: A Survey on Recent Research Progress and Challenges

Event is a common but non-negligible knowledge type. How to identify events from texts, extract their arguments, even analyze the relations between different events are important for many applications....

Share article

A comprehensive review on resolving ambiguities in natural language processing

Natural language processing is a known technology behind the development of some widely known AI assistants such as: SIRI, Natasha, and Watson. However, NLP is a diverse technology used for numerous...

Share article

The road from MLE to EM to VAE: A brief tutorial

Variational Auto-Encoders (VAEs) have emerged as one of the most popular genres of generative models, which are learned to characterize the data distribution. The classic Expectation Maximization (EM)...

Share article

Robustness of deep learning models on graphs: A survey

Machine learning (ML) technologies have achieved significant success in various downstream tasks, e.g., node classification, link prediction, community detection, graph classification and graph clustering....

Share article

Lawformer: A pre-trained language model for Chinese legal long documents

Legal artificial intelligence (LegalAI) aims to benefit legal systems with the technology of artificial intelligence, especially natural language processing (NLP). Recently, inspired by the success...

Share article

Discrete and continuous representations and processing in deep learning: Looking forward

Discrete and continuous representations of content (e.g., of language or images) have interesting properties to be explored for the understanding of or reasoning with this content by machines. This...

Share article

CPM-2: Large-scale cost-effective pre-trained language models

In recent years, the size of pre-trained language models (PLMs) has grown by leaps and bounds. However, efficiency issues of these large-scale PLMs limit their utilization in real-world scenarios. We...

Share article

A review of deep learning in question answering over knowledge bases

Question answering over knowledge bases (KBQA) is a challenging task in natural language processing. It requires machines to answer natural language questions based on large-scale knowledge bases. Recent...

Share article

WuDaoCorpora: A super large-scale Chinese corpora for pre-training language models

Using large-scale training data to build a pre-trained language model (PLM) with a larger volume of parameters can significantly improve downstream tasks. For example, OpenAI trained the GPT3 model...

Share article

AI-driven drug discovery: A boon against COVID-19?

The COVID-19 is an issue of international concern and threat to public health and there is an urgent need of drug/vaccine design. There is no vaccine or specific drug yet made as of July 23, 2020, for...

Share article

CokeBERT: Contextual knowledge selection and embedding towards enhanced pre-trained language models

Several recent efforts have been devoted to enhancing pre-trained language models (PLMs) by utilizing extra heterogeneous knowledge in knowledge graphs (KGs), and achieved consistent improvements on...

Share article

Heterogeneous graph knowledge enhanced stock market prediction

We focus on the task of stock market prediction based on financial text which contains information that could influence the movement of stock market. Previous works mainly utilize a single semantic...

Share article

Network representation learning: A macro and micro view

Abstract...

Share article

Stay Informed

Register your interest and receive email alerts tailored to your needs. Sign up below.