most citedBreaking the Static Graph: Context-Aware Traversal for Robust Retrieval-Augmented Generation

1 citations · 1 across the 2 of their papers we have counts for

collaborators

6 papers

cs.CL20261 cited

Breaking the Static Graph: Context-Aware Traversal for Robust Retrieval-Augmented Generation

Kwun Hang Lau, Fangyuan Zhang, Boyu Ruan +4

Recent advances in Retrieval-Augmented Generation (RAG) have shifted from simple vector similarity to structure-aware approaches like HippoRAG, which leverage Knowledge Graphs (KGs…

cs.DB2025

ACGraph: An Efficient Asynchronous Out-of-Core Graph Processing Framework

Dechuang Chen, Sibo Wang, Qintian Guo

Graphs are a ubiquitous data structure in diverse domains such as machine learning, social networks, and data mining. As real-world graphs continue to grow beyond the memory capaci…

cs.IR2025

LiCoMemory: Lightweight and Cognitive Agentic Memory for Efficient Long-Term Reasoning

Zhengjun Huang, Zhoujin Tian, Qintian Guo +5

Large Language Model (LLM) agents exhibit remarkable conversational and reasoning capabilities but remain constrained by limited context windows and the lack of persistent memory.…

cs.SD2025

Contextualized Token Discrimination for Speech Search Query Correction

Junyu Lu, Di Jiang, Mengze Hong +3

Query spelling correction is an important function of modern search engines since it effectively helps users express their intentions clearly. With the growing popularity of speech…

cs.IR2025

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…

cs.DS2025

Optimal Approximate Matrix Multiplication over Sliding Window

Haoming Xian, Qintian Guo, Jun Zhang +1

Matrix multiplication is a core operation in numerous applications, yet its exact computation becomes prohibitively expensive as data scales, especially in streaming environments w…