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cs.CL2025
ReFactX: Scalable Reasoning with Reliable Facts via Constrained Generation
Riccardo Pozzi, Matteo Palmonari, Andrea Coletta +3
Knowledge gaps and hallucinations are persistent challenges for Large Language Models (LLMs), which generate unreliable responses when lacking the necessary information to fulfill…
cs.CL2025
Aligning Knowledge Graphs and Language Models for Factual Accuracy
Nur A Zarin Nishat, Andrea Coletta, Luigi Bellomarini +3
Large language models like GPT-4, Gemini, and Claude have transformed natural language processing (NLP) tasks such as question answering, dialogue generation, summarization, and so…
cs.LG2025
SMART: Relation-Aware Learning of Geometric Representations for Knowledge Graphs
Kossi Amouzouvi, Bowen Song, Andrea Coletta +3
Knowledge graph representation learning approaches provide a mapping between symbolic knowledge in the form of triples in a knowledge graph (KG) and their feature vectors. Knowledg…