Overview of the Fifth Workshop on Scholarly Document Processing (2025)

Abstract: The workshop on Scholarly Document Processing (SDP) started in 2020 to accelerate research, inform policy, and educate the public on natural language processing for scientific text. The fifth iteration of the workshop, SDP 2025 was held at the 63rd Annual Meeting of the Association for Computational Linguistics (ACL 2025) in Vienna as a hybrid event. The workshop saw a great increase in interest, with 26 submissions, of which 11 were accepted for the research track. The program consisted of a research track, invited talks and four shared tasks: (1) SciHal25: Hallucination Detection for Scientific Content, (2) SciVQA: Scientific Visual Question Answering, (3) ClimateCheck: Scientific Factchecking of Social Media Posts on Climate Change, and (4) Software Mention Detection in Scholarly Publications (SOMD 25). In addition to the four shared task overview papers, 18 shared task reports were accepted. The program was geared towards NLP, information extraction, information retrieval, and data mining for scholarly documents, with an emphasis on identifying and providing solutions to open challenges.

## program the sdp 2025 workshop consisted of keynote talks, a research track and a shared task track. sdp 2025 received 26 submissions for the research track, of which 11 were accepted (42% acceptance rate). since the workshop will be hybrid, there will be both in-person and virtual presentations at the conference venue and online. topics of the presentations run the gamut, and include: scientific misconduct detection, scholarly impact prediction, novelty assessment in scientific literature, information extraction from scientific pdfs, dataset reference extraction, citation and document attribution, literature discovery via natural language queries, mathematical term disambiguation, latex code generation evaluation, clinical trial translation prediction, climate misinformation mapping, abstract screening in systematic reviews. as expected, we see a sharp increase in papers that employ large language models for downstream sdp tasks. the full program with links to papers, videos and posters is available at https://sdproc.org/2025/program.html . ## workshop review and outlook sdp is evolving along with other fields of ai. the increasing maturity of generative llms provides new opportunities and poses new challenges. the way in which tasks traditionally associated with literature mining are addressed has changed dramatically over the life of the workshop series. generative ai has not obviated tasks such as retrieval, extraction, and summarization, but has enabled researchers to explore interesting variants of these tasks and to shift focus from understanding to prediction. the same burgeoning of research, attributable to generative ai's democratizing effect, has created new problems for the conduct of science, raising interest in automated support for peer review and the enforcement of scholarly in-tegrity. as we consider future iterations of the workshop, we are discussing ways to respond to these trends. with sdp 2025 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 use and meta-linguistic aspects of scholarly communication. ## conclusion the workshop on scholarly document processing is part of a virtual cycle. advances in sdp have given rise to powerful new tools, such as google's co-scientist or elsevier's sciencedirect ai, that derive value from the communications of scholars and return value to scholars through sophisticated new forms of research facilitation. to the extent that these tools succeed, both the pace of scholarly discovery and the volume of scholarly communication will increase. but sdp research is not just an amplifier. we believe and hope that the research fostered at our workshop will open new lines of inquiry across a range of disciplines and relieve scientists of tedious or rote aspects of their labor. we hope that our work will ultimately increase the number and diversity of people that can make meaningful scholarly contributions.