During natural disasters, people often use social media platforms such a...
Many software projects implement APIs and algorithms in multiple program...
Understanding what leads to emotions during large-scale crises is import...
While existing work on studying bias in NLP focues on negative or pejora...
The rise of large language models (LLMs) has brought a critical need for...
Automated text simplification aims to produce simple versions of complex...
Automated text simplification, a technique useful for making text more
a...
Large language models, particularly GPT-3, are able to produce high qual...
Writing tests is a time-consuming yet essential task during software
dev...
Automatically fixing software bugs is a challenging task. While recent w...
Crises such as the COVID-19 pandemic continuously threaten our world and...
Automatic discourse processing, which can help understand how sentences
...
The recent success of zero- and few-shot prompting with models like GPT-...
Access to higher education is critical for minority populations and emer...
Pretrained language models have been shown to be effective in many
softw...
Developing methods to adversarially challenge NLP systems is a promising...
Progress in summarizing long texts is inhibited by the lack of appropria...
Automated simplification models aim to make input texts more readable. S...
We present ProtoTEx, a novel white-box NLP classification architecture b...
Long-form answers, consisting of multiple sentences, can provide nuanced...
While there has been substantial progress in text comprehension through
...
Pre-trained language models (e.g. BART) have shown impressive results wh...
When a software bug is reported, developers engage in a discussion to
co...
Deep-learning based Automatic Essay Scoring (AES) systems are being acti...
Fact-checking is the process (human, automated, or hybrid) by which clai...
There has been a growing interest in developing machine learning (ML) mo...
Crises such as natural disasters, global pandemics, and social unrest
co...
We consider the problem of learning to simplify medical texts. This is
i...
Discourse signals are often implicit, leaving it up to the interpreter t...
Descriptive code comments are essential for supporting code comprehensio...
Naming conventions are an important concern in large verification projec...
Significant progress has been made in deep-learning based Automatic Essa...
Much of modern day text simplification research focuses on sentence-leve...
Humans use language to accomplish a wide variety of tasks - asking for a...
Inquisitive probing questions come naturally to humans in a variety of
s...
Natural language comments convey key aspects of source code such as
impl...
Should the final right bracket in a record declaration be on a separate ...
Natural disasters (e.g., hurricanes) affect millions of people each year...
Recent advances in NLP have been attributed to the emergence of large-sc...
Recent advances in NLP have been attributed to the emergence of large-sc...
We formulate the novel task of automatically updating an existing natura...
Coding conventions for naming, spacing, and other essentially stylistic
...
Implicit discourse relations are not only more challenging to classify, ...
Comments are an integral part of software development; they are natural
...
This paper presents a data-driven study focusing on analyzing and predic...
Insightful findings in political science often require researchers to an...
Discourse structure is integral to understanding a text and is helpful i...
Unilateral contracts, such as terms of service, play a substantial role ...
The first step in discourse analysis involves dividing a text into segme...
Sentence specificity quantifies the level of detail in a sentence,
chara...