Author

Xiaochen Wang

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Jul 2026

KAMR: Grounding Generation via Knowledge-Aligned Multi-hop Retrieval

Graph-based retrieval-augmented generation increasingly relies on multi-hop retrieval, where answering a query requires composing multiple connected knowledge-graph triplets. However, existing retrievers often rank triplets independently via global semantic matching. Moreover, many multi-hop benchmarks provide only fin...

Xiaochen Wang, Yuan Zhong, Haoyu Wang et al. · arXiv.org · 0 citations

Preprint Aug 2026

Multi-Granularity Context-Enhanced RAG over Multimodal Knowledge Graphs

Retrieval-augmented generation (RAG) is widely used to mitigate hallucination issues in large language models (LLMs) and multimodal large language models (MLLMs). In particular, knowledge graph (KG)-based RAG leverages structured knowledge to provide (M)LLMs with high-quality external information. Building on these wor...

Zongyu Wu, Yilong Wang, Xiaochen Wang et al. · 0 citations