Essay scoring is a critical task used to evaluate second-language (L2) writing proficiency on
high-stakes language assessments. While automated scoring approaches are mature and …

We explore methods to extract relations between named entities from free text in an
unsupervised setting. In addition to standard feature extraction, we develop a novel method …

Automated Essay Scoring automates the grading process of essays, providing a great
advantage for improving the writing proficiency of students. While holistic essay scoring …

The training objective of neural machine translation (NMT) is to minimize the loss between
the words in the translated sentences and those in the references. In NMT, there is a natural …

In this study, we developed an off-topic response detection system to be used in the context
of the automated scoring of nonnative English speakers' spontaneous speech. Based on …

Advances in automated essay grading over the last sixty years enabled its application in real
scenarios, such as classrooms and high-stakes testing. The recognition of off-topic essays is …

Rapid advances in artificial intelligence (AI), specifically large language models (LLMs),
have recently generated significant debate. This article explores the impact of these …

Co-occurrences between two words provide useful insights into the semantics of those
words. Consequently, numerous prior work on word embedding learning has used co …

In neural machine translation (NMT), there is a natural correspondence between source and
target sentences. The traditional NMT method does not explicitly model the translation …

We have proposed a novel approach to automated essay scoring based on recurrent and
convolutional neural networks. Unlike existing systems, our approach does not rely on …