The task of resolving repeated objects in natural languages is known as coreference
resolution, and it is an important part of modern natural language processing. It is classified …

Semantic processing is a fundamental research domain in computational linguistics. In the
era of powerful pre-trained language models and large language models, the advancement …

Abstract Entity Coreference Resolution is the task of resolving all mentions in a document
that refer to the same real world entity and is considered as one of the most difficult tasks in …

While coreference resolution is defined independently of dataset domain, most models for
performing coreference resolution do not transfer well to unseen domains. We consolidate a …

Coreference resolution of geological entities is an important task in geological information
mining. Although the existing generic coreference resolution models can handle geological …

Semantic parsing (SP) allows humans to leverage vast knowledge resources through
natural interaction. However, parsers are mostly designed for and evaluated on English …

Abstract Bias in Artificial Intelligence (AI) is a critical and timely issue due to its sociological,
economic and legal impact, as decisions made by biased algorithms could lead to unfair …

The limited generalization of coreference resolution (CR) models has been a major
bottleneck in the task's broad application. Prior work has identified annotation differences …

Land-use regression (LUR) models are important for the assessment of air pollution
concentrations in areas without measurement stations. While many such models exist, they …

The limited generalization of coreference resolution (CR) models has been a major
bottleneck in the task's broad application. Prior work has identified annotation differences …