Sentiment analysis is a growing field at the intersection of linguistics and computer science
that attempts to automatically determine the sentiment contained in text. Sentiment can be …

Despite the recent success of deep neural networks in natural language processing and
other spheres of artificial intelligence, their interpretability remains a challenge. We analyze …

Abstract The Joint Conference on Lexical and Computational Semantics (* SEM) each year
hosts a shared task on semantic related topics. In its first edition held in 2012, the shared …

Automatic negation scope detection is a task that has been tackled using different classifiers
and heuristics. Most systems are however 1) highly-engineered, 2) English-specific, and 3) …

The study of evaluation, affect, and subjectivity is a multidisciplinary enterprise, including
sociology, psychology, economics, linguistics, and computer science. A number of excellent …

We consider the end-to-end abstract-to-title generation problem, exploring seven recent
transformer based models (including ChatGPT) fine-tuned on more than 30k abstract-title …

Speculation and negation are important information to identify text factuality. In this paper,
we propose a Convolutional Neural Network (CNN)-based model with probabilistic …

Recognizing negative and speculative information is highly relevant for sentiment analysis.
This paper presents a machine‐learning approach to automatically detect this kind of …

Negation is a universal linguistic phenomenon with a great qualitative impact on natural
language processing applications. The availability of corpora annotated with negation is …

Abstract Knowledge tracing aims to estimate students' knowledge state or skill mastering
level over time, which is evolving into an essential task in educational technology …