4 papers
SPARC-RAG: Adaptive Sequential-Parallel Scaling with Context Management for Retrieval-Augmented Generation
Yuxin Yang, Gangda Deng, Ömer Faruk Akgül +6
Retrieval-Augmented Generation (RAG) grounds large language model outputs in external evidence, but remains challenged on multi-hop question answering that requires long reasoning.…
Training Diverse Graph Experts for Ensembles: A Systematic Empirical Study
Gangda Deng, Yuxin Yang, Ömer Faruk Akgül +4
Graph Neural Networks (GNNs) have become essential tools for learning on relational data, yet the performance of a single GNN is often limited by the heterogeneity present in real-…
RECIPE-TKG: From Sparse History to Structured Reasoning for LLM-based Temporal Knowledge Graph Completion
Ömer Faruk Akgül, Feiyu Zhu, Yuxin Yang +2
Temporal Knowledge Graphs (TKGs) represent dynamic facts as timestamped relations between entities. TKG completion involves forecasting missing or future links, requiring models to…
Conformal Prediction for Federated Graph Neural Networks with Missing Neighbor Information
Ömer Faruk Akgül, Rajgopal Kannan, Viktor Prasanna
Graphs play a crucial role in data mining and machine learning, representing real-world objects and interactions. As graph datasets grow, managing large, decentralized subgraphs be…