9 papers
PolyUQuest: Verifiable Structure-Aware Web RAG over Heterogeneous Graphs
Ying Liu, Yi Ye, Quanyu Feng +5
Existing retrieval-augmented generation (RAG) systems treat web pages as flat text, losing the structural and semantic signals encoded in HTML. We present PolyUQuest, a verifiable,…
From Rigid to Dynamic: Entropy-Guided Adaptive Inference for Long-Context LLMs
Zhanchao Xu, Haoyang Li, Qingfa Xiao +4
Existing sparse attention and KV cache compression methods for long-context LLM inference typically apply fixed sparsity patterns or uniform budgets across all attention heads, ove…
Securing Retrieval-Augmented Generation: A Taxonomy of Attacks, Defenses, and Future Directions
Yuming Xu, Mingtao Zhang, Zhuohan Ge +7
Retrieval-augmented generation (RAG) extends large language models (LLMs) with external knowledge, but this access path also introduces security risks that existing work often conf…
OpenGLT: A Comprehensive Benchmark of Graph Neural Networks for Graph-Level Tasks
Haoyang Li, Yuming Xu, Alexander Zhou +4
Graphs are fundamental data structures for modeling complex interactions in domains such as social networks, molecular structures, and biological systems. Graph-level tasks, which…
GPU-Accelerated Algorithms for Graph Vector Search: Taxonomy, Empirical Study, and Research Directions
Yaowen Liu, Xuejia Chen, Anxin Tian +7
Approximate Nearest Neighbor Search (ANNS) underpins many large-scale data mining and machine learning applications, with efficient retrieval increasingly hinging on GPU accelerati…
LoopServe: An Adaptive Dual-phase LLM Inference Acceleration System for Multi-Turn Dialogues
Haoyang Li, Zhanchao Xu, Yiming Li +9
Multi-turn dialogues are essential in many real-world applications of large language models, such as chatbots and virtual assistants. As conversation histories become longer, exist…