2nd Workshop on Smarter Extraction of Scholarly Metadata Using Knowledge Graphs, Language Models and Agents (SESAME at JCDL 2026)

The 2nd Workshop on Smarter Extraction of Scholarly Metadata Using Knowledge Graphs, Language Models and Agents (SESAME), co-located with the ACM/IEEE Joint Conference on Digital Libraries (JCDL 2026), addresses the growing challenge of automatically extracting, enriching, and linking scholarly metadata at scale using modern AI technologies. The workshop examines how knowledge graphs, large language models, and autonomous agents can work in concert to improve the quality, completeness, and interoperability of bibliographic metadata across scientific publishing ecosystems. SESAME 2026 brings together researchers in digital libraries, information extraction, and AI to advance the infrastructure supporting open and findable scholarly knowledge.

NLP artificial intelligence

Submissions are invited on metadata extraction from scientific documents, knowledge graph construction for scholarly data, LLM-based information retrieval, entity linking and disambiguation, and agent-based approaches to scholarly metadata enrichment. Both full research papers and short system demonstrations are welcome.