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DocNavRAG: Document-Structured Graph RAG with Stateful Evidence Construction for Complex Document Question Answering
Dongyang Xie, Yao Tian, Hao Zhang +5
Answering complex questions over large document collections requires assembling complementary evidence across sections and documents. GraphRAG offers structured retrieval but typic…
AdaCultureSafe: Adaptive Cultural Safety Grounded by Cultural Knowledge in Large Language Models
Hankun Kang, Di Lin, Zhirong Liao +6
With the global proliferation of Large Language Models (LLMs), cultural safety, defined as the ability to generate respectful and appropriate responses across diverse cultures, bec…
A Survey on Training-free Alignment of Large Language Models
Birong Pan, Yongqi Li, Weiyu Zhang +6
The alignment of large language models (LLMs) aims to ensure their outputs adhere to human values, ethical standards, and legal norms. Traditional alignment methods often rely on r…
Format as a Prior: Quantifying and Analyzing Bias in LLMs for Heterogeneous Data
Jiacheng Liu, Mayi Xu, Qiankun Pi +5
Large Language Models (LLMs) are increasingly employed in applications that require processing information from heterogeneous formats, including texts, tables, infoboxes, and knowl…
Privacy-protected Retrieval-Augmented Generation for Knowledge Graph Question Answering
Yunfeng Ning, Mayi Xu, Jintao Wen +5
LLMs often suffer from hallucinations and outdated or incomplete knowledge. RAG is proposed to address these issues by integrating external knowledge like that in KGs into LLMs. Ho…