31 citations · 43 across the 14 of their papers we have counts for
4 papers · 1 filter
MMKG-R1: Constructing Multimodal Knowledge Graphs via Reinforcement Learning
Zongyu Wu, Yilong Wang, Xiaochen Wang +5
Multimodal knowledge graphs (MMKGs) organize information across different modalities to support multimodal Graph Retrieval-Augmented Generation (RAG), which aims to improve the per…
Multi-Granularity Context-Enhanced RAG over Multimodal Knowledge Graphs
Zongyu Wu, Yilong Wang, Xiaochen Wang +5
Retrieval-augmented generation (RAG) is widely used to mitigate hallucination issues in large language models (LLMs) and multimodal large language models (MLLMs). In particular, kn…
KAMR: Grounding Generation via Knowledge-Aligned Multi-hop Retrieval
Xiaochen Wang, Yuan Zhong, Haoyu Wang +2
Graph-based retrieval-augmented generation increasingly relies on multi-hop retrieval, where answering a query requires composing multiple connected knowledge-graph triplets. Howev…
MKG-RAG-Bench: Benchmarking Retrieval in Multimodal Knowledge Graph-Augmented Generation
Xiaochen Wang, Bao Hoang, Han Liu +2
Retrieval-augmented generation (RAG) over knowledge graphs has emerged as a promising approach for grounding large language models, yet existing benchmarks largely overlook the cha…