7 papers
Taming the Fragility of KV Cache Eviction in LLM Inference
Yuan Feng, Haoyu Guo, JunLin Lv +2
Large language models have revolutionized natural language processing, yet their deployment remains hampered by the substantial memory and runtime overhead of the transformer's Key…
See or Say Graphs: Agent-Driven Scalable Graph Structure Understanding with Vision-Language Models
Shuo Han, Yukun Cao, Zezhong Ding +3
Vision-language models (VLMs) have shown promise in graph structure understanding, but remain limited by input-token constraints, facing scalability bottlenecks and lacking effecti…
Lego Sketch: A Scalable Memory-augmented Neural Network for Sketching Data Streams
Yuan Feng, Yukun Cao, Hairu Wang +2
Sketches, probabilistic structures for estimating item frequencies in infinite data streams with limited space, are widely used across various domains. Recent studies have shifted…
SDD-4DGS: Static-Dynamic Aware Decoupling in Gaussian Splatting for 4D Scene Reconstruction
Dai Sun, Huhao Guan, Kun Zhang +2
Dynamic and static components in scenes often exhibit distinct properties, yet most 4D reconstruction methods treat them indiscriminately, leading to suboptimal performance in both…
FRAG: A Flexible Modular Framework for Retrieval-Augmented Generation based on Knowledge Graphs
Zengyi Gao, Yukun Cao, Hairu Wang +4
To mitigate the hallucination and knowledge deficiency in large language models (LLMs), Knowledge Graph (KG)-based Retrieval-Augmented Generation (RAG) has shown promising potentia…
LEGO-GraphRAG: Modularizing Graph-based Retrieval-Augmented Generation for Design Space Exploration
Yukun Cao, Zengyi Gao, Zhiyang Li +3
GraphRAG integrates (knowledge) graphs with large language models (LLMs) to improve reasoning accuracy and contextual relevance. Despite its promising applications and strong relev…