The exponential increase in scientific, technical, and legal data available on the Web, including research articles, patents, standards, and technical reports, has made their large-scale semantic processing, interlinking, and knowledge extraction a central challenge for the Web community. These data sources are heterogeneous, semi-structured, and domain-specific, containing complex elements such as text, tables, equations, and diagrams that make traditional data integration and analysis difficult. Yet, they hold immense potential for advancing knowledge discovery, open science, and evidence-based innovation. As the Web evolves into a vast ecosystem of human- and machine-generated content, there is a growing need to develop scalable AI models and semantic interoperable representations that transform this fragmented information into interconnected, machine-interpretable knowledge..
In this context, the SemTech 2026 workshop focuses on methods that combine Semantic Web technologies, Natural Language Processing, Large Language Models (LLMs), and other AI technologies to model knowledge across scientific, technical, and legal domains. The workshop invites research on knowledge graph creation, semantic annotation, LLM–KG hybrid reasoning, and trustworthy AI pipelines that enhance the reliability, interpretability, and reuse of Web data. This is particularly timely as the Web community seeks robust approaches to integrate symbolic and sub-symbolic methods for managing and understanding the growing body of domain-specific knowledge on the Web.
The workshop accepts contributions in all topics related to semantic web technologies and deep learning focused (but not limited) to:
There have been changes due to the conference policy
Formatting Requirements. Submissions must be written in English, in double-column format, and must adhere to the ACM template and format (also available in Overleaf ). Word users may use the Word Interim Template. The recommended setting for LaTeX is: \documentclass[sigconf, review]{acmart}
We will consider three different submission types:
Submissions should not exceed the indicated number of pages, including any diagrams and references.
The accepted papers will be available on the Workshop website. The proceedings shall be published in a CEUR-WS.org volume, which is free of charge for ALL authors. This publication is a "Diamond Open Access" service, meaning it is also free for all readers. The proceedings will be indexed on Google Scholar, DBLP, and Scopus as for the previous workshop editions.
CHANGE TO PROCEEDINGS PUBLICATION Due to conference policy, papers accepted by the workshop will be included in the Companion Proceedings of the Web Conference 2026 which are archived in the ACM Digital Library, subject to meeting the ACM open-access, formatting guidelines, and camera-ready timeline as provided and observed by the ACM Web Conference. See the section Important update on ACM's new open access publishing model for 2026 ACM Conferences! on the conference website.
Each submission will be reviewed by three independent reviewers on the basis of relevance for the workshop, novelty/originality, significance, technical quality and correctness, quality and clarity of presentation, quality of references and reproducibility.
All the information to register and attend the workshop can be found on the The Web Conf registration page.
SemTech4STLD workshop will take place on TBD.