GraphOracle: Efficient Fully-Inductive Knowledge Graph Reasoning via Relation-Dependency Graphs
Abstract Knowledge-graph reasoners often struggle when test-time entities and relations were never observed during training. GraphOracle addresses this fully-inductive setting by converting each knowledge graph into a directed Relation-Dependency Graph (RDG). The RDG captures how relations compose, and its query-aware embeddings guide answer prediction on the original entity graph.
Mar 25, 2025
MoKGR: Mixture of Length and Pruning Experts for Knowledge Graphs Reasoning
Abstract Knowledge-graph reasoning depends on finding the right paths—not simply exploring more of them. MoKGR personalizes graph traversal with two mixture-of-experts modules: one chooses an appropriate reasoning depth for each query, while the other decides which candidate paths deserve to survive.
Jan 19, 2025