Science across all disciplines has become increasingly data-driven, leading to additional
needs with respect to software for collecting, processing and analysing data. Thus …

Document-level relation extraction (RE) aims to extract the relation of entities that may be
across sentences. Existing methods mainly rely on two types of techniques: Pre-trained …

In this paper, we investigate progress toward improved software citation by examining
current software citation practices. We first introduce our machine learning based data …

The automatic extraction of materials and related properties from the scientific literature is
gaining attention in data-driven materials science (Materials Informatics). In this paper, we …

Accurately typing entity mentions from text segments is a fundamental task for various
natural language processing applications. Many previous approaches rely on massive …

There is today no standard way to reference research datasets and software in scientific
communication. Emerging editorial workflows and supporting infrastructures dedicated to …

This paper describes our systems for the sub-task I in the Software Mention Detection in
Scholarly Publications shared-task. We propose three approaches leveraging different pre …

This paper describes our systems for the sub-task I in the Software Mention Detection in
Scholarly Publications shared-task. We propose three approaches leveraging different pre …

Research software (ie, the tools and scripts developed as part of a research investigation)
are key to support the results described in academic publications. However, current citation …

This paper describes our systems for the sub-task I in the Software Mention Detection in
Scholarly Publications shared-task. We propose three approaches leveraging different pre …