activity
20192026
most citedTrans4E: Link Prediction on Scholarly Knowledge Graphs

61 citations · 231 across the 34 of their papers we have counts for

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Showing 2025Show all

6 papers · 1 filter

cs.AI2025

Geometric Structural Knowledge Graph Foundation Model

Ling Xin, Mojtaba Nayyeri, Zahra Makki Nayeri +1

Structural knowledge graph foundation models aim to generalize reasoning to completely new graphs with unseen entities and relations. A key limitation of existing approaches like U…

cs.AI2025

Full-History Graphs with Edge-Type Decoupled Networks for Temporal Reasoning

Osama Mohammed, Jiaxin Pan, Mojtaba Nayyeri +2

Modeling evolving interactions among entities is critical in many real-world tasks. For example, predicting driver maneuvers in traffic requires tracking how neighboring vehicles a…

cs.AI2025

Mathematical Reasoning for Unmanned Aerial Vehicles: A RAG-Based Approach for Complex Arithmetic Reasoning

Mehdi Azarafza, Mojtaba Nayyeri, Faezeh Pasandideh +2

Autonomous UAV operation necessitates reliable mathematical reasoning for tasks such as trajectory planning and power management. While traditional flight control relies on hardcod…

cs.AI2025

Towards Foundation Model on Temporal Knowledge Graph Reasoning

Jiaxin Pan, Mojtaba Nayyeri, Osama Mohammed +4

Temporal Knowledge Graphs (TKGs) store temporal facts with quadruple formats (s, p, o, t). Existing Temporal Knowledge Graph Embedding (TKGE) models perform link prediction tasks i…

cs.DB2025★ 1 cited

Retrieval-Augmented Generation of Ontologies from Relational Databases

Nadeen Fathallah, Mojtaba Nayyeri, Athish A Yogi +4

Deriving OWL ontologies from relational database schemas supports semantic interoperability and downstream tasks such as knowledge graph population, ontology-based data access, gra…

cs.CL2025

SEMMA: A Semantic Aware Knowledge Graph Foundation Model

Arvindh Arun, Sumit Kumar, Mojtaba Nayyeri +4

Knowledge Graph Foundation Models (KGFMs) have shown promise in enabling zero-shot reasoning over unseen graphs by learning transferable patterns. However, most existing KGFMs rely…