4 papers
Leveraging LLM-GNN Integration for Open-World Question Answering over Knowledge Graphs
Hussein Abdallah, Ibrahim Abdelaziz, Panos Kalnis +1
Open-world Question Answering (OW-QA) over knowledge graphs (KGs) aims to answer questions over incomplete or evolving KGs. Traditional KGQA assumes a closed world where answers mu…
Architectural Design, Not Only Model Intelligence, Governs Multi-Agent LLM Performance
Abdelghny Orogat, Ana Rostam, Essam Mansour
Multi-agent LLM frameworks are data-intensive systems that govern how agents orchestrate tasks, manage state, and coordinate decisions. These architectural choices control executio…
Chatty-KG: A Multi-Agent AI System for On-Demand Conversational Question Answering over Knowledge Graphs
Reham Omar, Abdelghny Orogat, Ibrahim Abdelaziz +3
Conversational Question Answering over Knowledge Graphs (KGs) combines the factual grounding of KG-based QA with the interactive nature of dialogue systems. KGs are widely used in…
Task-Oriented GNNs Training on Large Knowledge Graphs for Accurate and Efficient Modeling
Hussein Abdallah, Waleed Afandi, Panos Kalnis +1
A Knowledge Graph (KG) is a heterogeneous graph encompassing a diverse range of node and edge types. Heterogeneous Graph Neural Networks (HGNNs) are popular for training machine le…