Papers by Fenglong Su
Temporal Extrapolation and Knowledge Transfer for Lifelong Temporal Knowledge Graph Reasoning (2023.findings-emnlp)
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| Challenge: | Existing methods for lifelong TKG reasoning only address part of the challenges. |
| Approach: | They propose a temporal-path-based reinforcement learning framework for lifelong TKG reasoning . they add temporal displacement into the action space of RL to extrapolate for the future . |
| Outcome: | The proposed model outperforms existing models against well-adapted baselines on three lifelong TKG reasoning benchmarks. |
Time-aware Graph Neural Network for Entity Alignment between Temporal Knowledge Graphs (2021.emnlp-main)
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| Challenge: | Existing embedding-based approaches disregard time information that exists in many large-scale knowledge graphs, leaving much room for improvement. |
| Approach: | They propose a Time-aware Entity Alignment approach that incorporates relation and time information into a vector space and uses Graph Neural Networks to learn entity representations. |
| Outcome: | The proposed approach outperforms the state-of-the-art methods on real-world TKG datasets due to the inclusion of time information. |