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Found 8 papers, 2 papers with code
Cross-Care: Assessing the Healthcare Implications of Pre-training Data on Language Model Bias
Large language models (LLMs) are increasingly essential in processing natural languages, yet their application is frequently compromised by biases and inaccuracies originating in their training data.
Knowledge Graphs for the Life Sciences: Recent Developments, Challenges and Opportunities
The term life sciences refers to the disciplines that study living organisms and life processes, and include chemistry, biology, medicine, and a range of other related disciplines.
Ontology Pre-training for Poison Prediction
Integrating human knowledge into neural networks has the potential to improve their robustness and interpretability.
Ontology Development is Consensus Creation, Not (Merely) Representation
Ontology development methodologies emphasise knowledge gathering from domain experts and documentary resources, and knowledge representation using an ontology language such as OWL or FOL.
When one Logic is Not Enough: Integrating First-order Annotations in OWL Ontologies
In ontology development, there is a gap between domain ontologies which mostly use the web ontology language, OWL, and foundational ontologies written in first-order logic, FOL.
ESC-Rules: Explainable, Semantically Constrained Rule Sets
We describe a novel approach to explainable prediction of a continuous variable based on learning fuzzy weighted rules.
Automated and Explainable Ontology Extension Based on Deep Learning: A Case Study in the Chemical Domain
We present a new methodology for automatic ontology extension and apply it to the ChEBI ontology, a prominent reference ontology for life sciences chemistry.
The Literary Theme Ontology for Media Annotation and Information Retrieval
Literary theme identification and interpretation is a focal point of literary studies scholarship.
