3 accepted papers
Fair dynamic graph embedding is crucial for real-world systems, such as recommendation and social networks. Prior studies impose a single-axis fairness formulation, treating attribute and structural bias as separable artifacts. This overlooks their coupling relationship, under which debiasing along
The integration of knowledge graphs (KGs) with large language models (LLMs) offers significant potential to enhance the retrieval stage in retrieval-augmented generation (RAG) systems. In this study, we propose KG-CQR, a novel framework for Contextual Query Retrieval (CQR) that enhances the retrieva
This study aims to represent stories in narrative works (i.e., creative works that contain stories) with a fixed-length vector. We apply subgraph-based graph embedding models to dynamic social networks of characters that appeared in stories (character networks). We suppose that interactions between…