3 papers
cs.AI2026
ImbalancE: Inference-Time Latent Search Against Degree Imbalance in Link Prediction
Alberto Bernardi, Luca Costabello, Christophe Gueret
Knowledge Graph Embedding models have been extensively used to learn representations of entities and relations in Knowledge Graphs for predicting missing links. However, the qualit…
cs.AI2025
Interactive Query Answering on Knowledge Graphs with Soft Entity Constraints
Daniel Daza, Alberto Bernardi, Luca Costabello +4
Methods for query answering over incomplete knowledge graphs retrieve entities that are likely to be answers, which is particularly useful when such answers cannot be reached by di…
cs.AI2024
Domain and Range Aware Synthetic Negatives Generation for Knowledge Graph Embedding Models
Alberto Bernardi, Luca Costabello
Knowledge Graph Embedding models, representing entities and edges in a low-dimensional space, have been extremely successful at solving tasks related to completing and exploring Kn…