Abstract Natural Language Processing (NLP) is one of the most captivating applications of
Deep Learning. In this survey, we consider how the Data Augmentation training strategy can …

The struggle of social media platforms to moderate content in a timely manner, encourages
users to abuse such platforms to spread vulgar or abusive language, which, when …

Information overload is a major obstacle to scientific progress. The explosive growth in
scientific literature and data has made it ever harder to discover useful insights in a large …

In the summarization domain, a key requirement for summaries is to be factually consistent
with the input document. Previous work has found that natural language inference (NLI) …

Since the release of T\" ULU [Wang et al., 2023b], open resources for instruction tuning have
developed quickly, from better base models to new finetuning techniques. We test and …

We study the problem of retrieval with instructions, where users of a retrieval system
explicitly describe their intent along with their queries. We aim to develop a general-purpose …

The volume of scientific output is creating an urgent need for automated tools to help
scientists keep up with developments in their field. Semantic Scholar (S2) is an open data …

To assess the effectiveness of any medical intervention, researchers must conduct a time-
intensive and highly manual literature review. NLP systems can help to automate or assist in …

The rapid development of science and technology has been accompanied by an
exponential growth in peer-reviewed scientific publications. At the same time, the review of …

Scholars who want to research a scientific topic must take time to read, extract meaning, and
identify connections across many papers. As scientific literature grows, this becomes …