Our keynote speakers will highlight significant research and challenges in scholarly document processing.
The workshop will host four shared tasks spanning document summarization, scientific fact checking, and citation context classification.
Topics of interest, formatting and submission instructions, and important dates.
As the body of scholarly literature grows, automated methods in NLP, text mining, information retrieval, document understanding etc. are needed to address issues of information overload, disinformation, reproducibility, and more. Though progress has been made, there are significant unique challenges to processing scholarly text that require dedicated attention. The goal of this workshop is to provide a venue for addressing these challenges, as well as a platform for tasks and resources supporting the processing of scientific documents. Our long-term objective is to establish scholarly and scientific texts as an essential domain for NLP research, to supplement current efforts on web text and news articles.
This workshop builds on the success of prior workshops: the 1st SDP workshop (to be held at EMNLP 2020), and the 1st SciNLP workshop held at AKBC 2020. Both workshops received numerous submissions and were/will presumably be well attended, demonstrating that interest in this area seems to be growing rapidly. In addition to having broad appeal within the NLP community, we expect that the SDP workshop will attract researchers from other relevant fields including meta-science, scientometrics, data mining, information retrieval, and digital libraries, bringing together these disparate communities within the ACL.
|Notification of paper acceptance||TBA|
|Camera-ready submission of accepted papers||TBA|