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Continual Multimodal Knowledge Graph Construction

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arxiv 2305.08698 v3 pith:KW4VAJ7B submitted 2023-05-15 cs.CL cs.AIcs.DBcs.LGcs.MM

Continual Multimodal Knowledge Graph Construction

Xiang Chen , Jintian Zhang , Xiaohan Wang , Ningyu Zhang , Tongtong Wu , Yuxiang Wang , Yongheng Wang , Huajun Chen This is my paper
classification cs.CL cs.AIcs.DBcs.LGcs.MM
keywords knowledgecontinualmkgcmsptmultimodalconstructioncurrentdata
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved
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Current Multimodal Knowledge Graph Construction (MKGC) models struggle with the real-world dynamism of continuously emerging entities and relations, often succumbing to catastrophic forgetting-loss of previously acquired knowledge. This study introduces benchmarks aimed at fostering the development of the continual MKGC domain. We further introduce MSPT framework, designed to surmount the shortcomings of existing MKGC approaches during multimedia data processing. MSPT harmonizes the retention of learned knowledge (stability) and the integration of new data (plasticity), outperforming current continual learning and multimodal methods. Our results confirm MSPT's superior performance in evolving knowledge environments, showcasing its capacity to navigate balance between stability and plasticity.

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Cited by 3 Pith papers

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  3. Multi-Faceted Continual Knowledge Graph Embedding for Semantic-Aware Link Prediction

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