FedV-KGQA: Multi-Hop Question Answering over Vertically Partitioned Knowledge Graphs

arXiv:2608.24846 · cs.AI · Submitted 2026-08-25 · Read on arXiv

cs.AI

Submitted: 2026-08-25

Updated: 2026-08-25

Comments: Accepted at ISWC 2026 (Research Track). To appear in the Proceedings of the 25th International Semantic Web Conference

Code: https://github.com/brains-group/fedv-kgqa-source

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Knowledge Graph — 39× in this paper · explained in 7 episodes
• Embeddings — 26× in this paper · explained in 2 episodes
• Knowledge graphs — 14× in this paper · explained in 2 episodes
• Benchmark — 13× in this paper · explained in 2 episodes
• Federated Learning — 12× in this paper · explained in 14 episodes
• Axioms — 9× in this paper · explained in 2 episodes
• Actor — 7× in this paper · explained in 3 episodes
• Multi-hop Reasoning — 6× in this paper · explained in 3 episodes
• Accuracy — 4× in this paper · explained in 1 episode
• Aggregation — 4× in this paper · explained in 1 episode
• Robustness — 4× in this paper · explained in 5 episodes
• Ablation — 3× in this paper · explained in 1 episode
• Ablation study — 3× in this paper · explained in 1 episode
• Data Sovereignty — 3× in this paper · explained in 2 episodes
• Adam — 2× in this paper · explained in 2 episodes
• Differentially Private — 2× in this paper · explained in 3 episodes
• Transformer — 2× in this paper · explained in 2 episodes
• Alignment — 1× in this paper · explained in 1 episode
• Calibration — 1× in this paper · explained in 7 episodes
• Contrastive Learning — 1× in this paper · explained in 5 episodes
• Core — 1× in this paper · explained in 2 episodes
• Cosine Similarity — 1× in this paper · explained in 3 episodes
• Differential Privacy — 1× in this paper · explained in 4 episodes
• Differential Privacy (DP) — 1× in this paper · explained in 7 episodes
• Federated Learning (FL) — 1× in this paper · explained in 7 episodes
• Generalization — 1× in this paper · explained in 13 episodes
• Generative AI — 1× in this paper · explained in 2 episodes
• Grounding — 1× in this paper · explained in 3 episodes
• Large Language Models (LLMs) — 1× in this paper · explained in 6 episodes
• Mean Reciprocal Rank — 1× in this paper

Sources

• RoBERTa: A Robustly Optimized BERT Pretraining Approach
• DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lighter
• RotatE: Knowledge Graph Embedding by Relational Rotation in Complex Space
• Embedding Entities and Relations for Learning and Inference in Knowledge Bases

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