Scholarly metadata is an essential element in the scholarly ecosystem, empowering discovery, interoperability, and provenance and its efficacy relies on metadata quality and coverage. However, with the substantial increase in the number and diversity of research artifacts over time, it has become a cumbersome task to h...
Muhammad Asif Suryani, Brigitte Mathiak, Florian Reitz et al.· Proceedings of the 26th ACM/...· 0 citations
Extreme multi-label classification (XML) and hierarchical text classification (HTC) address closely related multi-label prediction problems, but have largely developed as separate research areas. XML focuses on very large label spaces and typically evaluates ranked label lists, while HTC assumes a human-curated label h...
Florian Hauss, Tom Speier, Nerijus Bertalis et al.· Proceedings of the 2026 ACM...· 0 citations
This paper proposes GLaMoR (Graph Language Model for Reasoning), a reasoning pipeline that transforms OWL ontologies into graph-structured data and adapts the GLM architecture for consistency checking and shows that the GLM outperforms all baseline models, achieving 95% accuracy and is 20 times faster than classical re...
Chimaera integrates mixture-of-experts with graph foundation models (GFM) and integrates different GFM architectures, such as graph prompts and linear GNN models, to extend existing linear GNNs to support link-level and graph-level tasks in addition to node-level tasks.
John P. Frank, David Richerby, A. Scherp· 0 citations
Two language-model-based strategies are proposed for semantic code document segmentation, including a line-by-line approach that classifies each line of code separately before grouping the results into functional units, and a range-based approach that aims to directly determine groups of code lines from the input.
A. Dahou, A. Scherp, Sebastian Kurten et al.· Proceedings of the 2026 ACM...· 0 citations
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