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cs.AI2024
Context-aware Inductive Knowledge Graph Completion with Latent Type Constraints and Subgraph Reasoning
Muzhi Li, Cehao Yang, Chengjin Xu +5
Inductive knowledge graph completion (KGC) aims to predict missing triples with unseen entities. Recent works focus on modeling reasoning paths between the head and tail entity as…
cs.CL2024
Financial Knowledge Large Language Model
Cehao Yang, Chengjin Xu, Yiyan Qi
Artificial intelligence is making significant strides in the finance industry, revolutionizing how data is processed and interpreted. Among these technologies, large language model…
cs.AI2024
Context Graph
Chengjin Xu, Muzhi Li, Cehao Yang +4
Knowledge Graphs (KGs) are foundational structures in many AI applications, representing entities and their interrelations through triples. However, triple-based KGs lack the conte…