5 papers
BookRAG: A Hierarchical Structure-aware Index-based Approach for Retrieval-Augmented Generation on Complex Documents
Shu Wang, Yingli Zhou, Yixiang Fang
As an effective method to boost the performance of Large Language Models (LLMs) on the question answering (QA) task, Retrieval-Augmented Generation (RAG), which queries highly rele…
EraRAG: Efficient and Incremental Retrieval Augmented Generation for Growing Corpora
Fangyuan Zhang, Zhengjun Huang, Yingli Zhou +6
Graph-based Retrieval-Augmented Generation (Graph-RAG) enhances large language models (LLMs) by structuring retrieval over an external corpus. However, existing approaches typicall…
Clue-RAG: Towards Accurate and Cost-Efficient Graph-based RAG via Multi-Partite Graph and Query-Driven Iterative Retrieval
Yaodong Su, Yixiang Fang, Yingli Zhou +2
Despite the remarkable progress of Large Language Models (LLMs), their performance in question answering (QA) remains limited by the lack of domain-specific and up-to-date knowledg…
UTCS: Effective Unsupervised Temporal Community Search with Pre-training of Temporal Dynamics and Subgraph Knowledge
Yue Zhang, Yankai Chen, Yingli Zhou +3
In many real-world applications, the evolving relationships between entities can be modeled as temporal graphs, where each edge has a timestamp representing the interaction time. A…
Scalable Approximate Biclique Counting over Large Bipartite Graphs
Jingbang Chen, Weinuo Li, Yingli Zhou +5
Counting -bicliques in bipartite graphs is crucial for a variety of applications, from recommendation systems to cohesive subgraph analysis. Yet, it remains computationally…