Papers by Chu-song Chen

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Challenge:	Existing RAG solutions for large language models are limited by context windows limiting their ability to process long-form, domain-specific content.
Approach:	They propose a multimodal knowledge graph-based RAG that enables cross-modal reasoning . their method incorporates visual cues into the construction of knowledge graphs, retrieval phase, and answer generation process .
Outcome:	Experimental results show that the proposed approach outperforms existing approaches on textual and multimodal benchmarks.