Graph neural networks: A review of methods and applications
2020
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,...
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A survey of transformers
2022
Transformers have achieved great success in many artificial intelligence fields, such as natural language processing, computer vision, and audio processing. Therefore, it is natural to attract lots...
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Pre-trained models: Past, present and future
2021
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...
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Deep learning for fake news detection: A comprehensive survey
2022
The information age enables people to obtain news online through various channels, yet in the meanwhile making false news spread at unprecedented speed. Fake news exerts detrimental effects for it impairs...
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GPT understands, too
Available online 26 August 2023
Prompting a pretrained language model with natural language patterns has been proved effective for natural language understanding (NLU). However, our preliminary study reveals that manual discrete prompts...
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Neural machine translation: A review of methods, resources, and tools
2020
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)...
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Data augmentation approaches in natural language processing: A survey
2022
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...
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A survey on complex factual question answering
2023
Answering complex factual questions has drawn a lot of attention. Researchers leverage various data sources to support complex QA, such as unstructured texts, structured knowledge graphs and relational...
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Sarcasm detection using news headlines dataset
2023
Sarcasm has been an elusive concept for humans. Due to interesting linguistic properties, sarcasm detection has gained traction of the Natural Language Processing (NLP) research community in the past...
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PTR: Prompt Tuning with Rules for Text Classification
2022
Recently, prompt tuning has been widely applied to stimulate the rich knowledge in pre-trained language models (PLMs) to serve NLP tasks. Although prompt tuning has achieved promising results on some...
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WuDaoCorpora: A super large-scale Chinese corpora for pre-training language models
2021
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...
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Advances and challenges in conversational recommender systems: A survey
2021
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...
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A comprehensive review on resolving ambiguities in natural language processing
2021
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...
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Semantic graph based topic modelling framework for multilingual fake news detection
2023
Fake news detection is one of the most alluring problems that has grabbed the interest of Machine Learning (ML) and Natural Language Processing (NLP) experts in recent years. The majority of existing...
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A comprehensive survey of entity alignment for knowledge graphs
2021
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...
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Neural, symbolic and neural-symbolic reasoning on knowledge graphs
2021
Knowledge graph reasoning is the fundamental component to support machine learning applications such as information extraction, information retrieval, and recommendation. Since knowledge graphs can...
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Human motion modeling with deep learning: A survey
2022
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...
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Learning towards conversational AI: A survey
2022
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...
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Lawformer: A pre-trained language model for Chinese legal long documents
2021
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...
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Extracting Events and Their Relations from Texts: A Survey on Recent Research Progress and Challenges
2020
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....
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Survey: Transformer based video-language pre-training
2022
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...
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Graph-based methods for cervical cancer segmentation: Advancements, limitations, and future directions
2023
Cervical cancer remains a significant health concern worldwide, where precise segmentation of cervical lesions is integral for effective diagnosis and treatment planning. This systematic review critically...
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Self-directed machine learning
2022
Conventional machine learning (ML) relies heavily on manual design from machine learning experts to decide learning tasks, data, models, optimization algorithms, and evaluation metrics, which is labor-intensive,...
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A survey on heterogeneous information network based recommender systems: Concepts, methods, applications and resources
2022
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,...
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