Machine knowledge: Creation and curation of comprehensive knowledge bases
Equip** machines with comprehensive knowledge of the world's entities and their
relationships has been a longstanding goal of AI. Over the last decade, large-scale …
relationships has been a longstanding goal of AI. Over the last decade, large-scale …
Academic plagiarism detection: a systematic literature review
This article summarizes the research on computational methods to detect academic
plagiarism by systematically reviewing 239 research papers published between 2013 and …
plagiarism by systematically reviewing 239 research papers published between 2013 and …
Auggpt: Leveraging chatgpt for text data augmentation
Text data augmentation is an effective strategy for overcoming the challenge of limited
sample sizes in many natural language processing (NLP) tasks. This challenge is especially …
sample sizes in many natural language processing (NLP) tasks. This challenge is especially …
A survey of data augmentation approaches for NLP
Data augmentation has recently seen increased interest in NLP due to more work in low-
resource domains, new tasks, and the popularity of large-scale neural networks that require …
resource domains, new tasks, and the popularity of large-scale neural networks that require …
[كتاب][B] Neural network methods in natural language processing
Y Goldberg - 2017 - books.google.com
Neural networks are a family of powerful machine learning models and this book focuses on
their application to natural language data. The first half of the book (Parts I and II) covers the …
their application to natural language data. The first half of the book (Parts I and II) covers the …
A large annotated corpus for learning natural language inference
Understanding entailment and contradiction is fundamental to understanding natural
language, and inference about entailment and contradiction is a valuable testing ground for …
language, and inference about entailment and contradiction is a valuable testing ground for …
Towards universal paraphrastic sentence embeddings
We consider the problem of learning general-purpose, paraphrastic sentence embeddings
based on supervision from the Paraphrase Database (Ganitkevitch et al., 2013). We …
based on supervision from the Paraphrase Database (Ganitkevitch et al., 2013). We …
Reside: Improving distantly-supervised neural relation extraction using side information
Distantly-supervised Relation Extraction (RE) methods train an extractor by automatically
aligning relation instances in a Knowledge Base (KB) with unstructured text. In addition to …
aligning relation instances in a Knowledge Base (KB) with unstructured text. In addition to …
From word to sense embeddings: A survey on vector representations of meaning
Over the past years, distributed semantic representations have proved to be effective and
flexible keepers of prior knowledge to be integrated into downstream applications. This …
flexible keepers of prior knowledge to be integrated into downstream applications. This …
Counter-fitting word vectors to linguistic constraints
In this work, we present a novel counter-fitting method which injects antonymy and
synonymy constraints into vector space representations in order to improve the vectors' …
synonymy constraints into vector space representations in order to improve the vectors' …