Towards a Learnable Retriever for Textual Graph Question Answering
Textual graph question answering (GraphQA) and graph-based retrieval-augmented generation (GraphRAG) have gained increasing attention as a way to ground large language models (LLMs) on structured knowledge. Despite extensive efforts, existing methods still face two key gaps. The first is an architectural gap: existing...
Kai-Feng Jin, Yu-Chen Yan, Zhichen Zeng et al.
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