Overview of the Second Workshop on Scholarly Document Processing (2021)

Abstract: With the ever-increasing pace of research and high volume of scholarly communication, scholars face a daunting task. Not only must they keep up with the growing literature in their own and related fields, scholars increasingly also need to rebut pseudo-science and disinformation. These needs have motivated an increasing focus on computational methods for enhancing search, summarization, and analysis of scholarly documents. However, the various strands of research on scholarly document processing remain fragmented. To reach out to the broader NLP and AI/ML community, pool distributed efforts in this area, and enable shared access to published research, we held the 2nd Workshop on Scholarly Document Processing (SDP) at NAACL 2021 as a virtual event ( https://sdproc.org/2021/ ). The SDP workshop consisted of a research track, three invited talks, and three Shared Tasks (LongSumm 2021, SCIVER, and 3C). The program was geared towards the application of NLP, information retrieval, and data mining for scholarly documents, with an emphasis on identifying and providing solutions to open challenges.

## research track in total, we received 26 submissions for the research track. we accepted 11 papers for presentation (5 as long papers and 6 as short papers). one accepted paper was withdrawn by the authors after notification. we rejected 15 research paper submissions. the accepted papers are: long papers: ## workshop overview and outlook the organizers were gratified by both the size and breadth of the response to the second edition of sdp. the subjects of accepted papers ranged from end uses of the scholarly literature (such as search, document expansion, or writing support) to challenges associated with automated understanding (such as metadata extraction and disambiguation or argument mining), to adaptations of recent successes in the broader field of nlp. it is apparent that automated processing of the scholarly literature is a problem that meets with substantial interest. and it seems likely that we are observing the beginnings of a research community with a narrow enough focus to make rapid progress, but a broad enough set of concerns to offer ample opportunities for cross-pollination. to a first approximation, we regard sdp as a confluence of three communities: nlp, information retrieval, and scientometrics. given our colocation with naacl, it is perhaps not surprising that the majority of our submissions emphasized nlp. as we consider future iterations of the workshop, we are discussing ways to increase its subject diversity. with sdp 2021 we have begun to present a more varied set of shared tasks, each highlighting challenges unique to the automated processing of the scholarly literature. as we proceed with planning and advertising, a key objective will be to elicit high-quality submissions from researchers interested in the uses and metalinguistic aspects of scholarly communication. ## conclusion the scholarly literature has long served as a rich source of interesting and challenging problems for computer science, and there is substantial prior work in information retrieval, scientometrics, data mining, and computational linguistics, but many important challenges remain. in many respects, our efforts to faithfully capture the semantics of scholarly communication through automated means are still in their infancy. at the same time, recent events regarding misinterpretation of scholarly information accentuate the importance of better approaches to the automated processing of scholarly literature. by drawing attention to these problems and offering a forum for interested scientists from a range of disciplines to collaborate, we hope that this and future instances of sdp encourage the application of recent advances in relevant fields to this problem area, identify new use cases or improve our understanding of existing ones, and ultimately foster solutions that improve the practice of scholarship and serve society.