Temporal-Aware Heterogeneous Graph Reasoning with Multi-View Fusion for Temporal Question Answering

• URL: http://arxiv.org/abs/2602.19569v1
• Date: Mon, 23 Feb 2026 07:36:36 GMT
• Title: Temporal-Aware Heterogeneous Graph Reasoning with Multi-View Fusion for Temporal Question Answering
• Authors: Wuzhenghong Wen, Bowen Zhou, Jinwen Huang, Xianjie Wu, Yuwei Sun, Su Pan, Liang Li, Jianting Liu,
• Abstract summary: We propose a novel framework with temporal-aware question encoding, multi-hop graph reasoning, and multi-view heterogeneous information fusion.<n>Specifically, our approach introduces: 1) a constraint-aware question representation that combines semantic cues from language models with temporal entity dynamics; 2) a temporal-aware graph neural network for explicit multi-hop reasoning via time-aware message passing; and 3) a multi-view attention mechanism for more effective fusion of question context and temporal graph knowledge.
• Score: 15.478564862251352
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Question Answering over Temporal Knowledge Graphs (TKGQA) has attracted growing interest for handling time-sensitive queries. However, existing methods still struggle with: 1) weak incorporation of temporal constraints in question representation, causing biased reasoning; 2) limited ability to perform explicit multi-hop reasoning; and 3) suboptimal fusion of language and graph representations. We propose a novel framework with temporal-aware question encoding, multi-hop graph reasoning, and multi-view heterogeneous information fusion. Specifically, our approach introduces: 1) a constraint-aware question representation that combines semantic cues from language models with temporal entity dynamics; 2) a temporal-aware graph neural network for explicit multi-hop reasoning via time-aware message passing; and 3) a multi-view attention mechanism for more effective fusion of question context and temporal graph knowledge. Experiments on multiple TKGQA benchmarks demonstrate consistent improvements over multiple baselines.

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