28 citations · 77 across the 28 of their papers we have counts for
7 papers · 1 filter
Zero-Shot Cellular Trajectory Map Matching
Weijie Shi, Yue Cui, Hao Chen +5
Cellular Trajectory Map-Matching (CTMM) aims to align cellular location sequences to road networks, which is a necessary preprocessing in location-based services on web platforms l…
A Pilot Empirical Study on When and How to Use Knowledge Graphs as Retrieval Augmented Generation
Xujie Yuan, Yongxu Liu, Shimin Di +6
The integration of Knowledge Graphs (KGs) into the Retrieval Augmented Generation (RAG) framework has attracted significant interest, with early studies showing promise in mitigati…
Top Ten Challenges Towards Agentic Neural Graph Databases
Jiaxin Bai, Zihao Wang, Yukun Zhou +16
Graph databases (GDBs) like Neo4j and TigerGraph excel at handling interconnected data but lack advanced inference capabilities. Neural Graph Databases (NGDBs) address this by inte…
Scene-Driven Multimodal Knowledge Graph Construction for Embodied AI
Song Yaoxian, Sun Penglei, Liu Haoyu +4
Embodied AI is one of the most popular studies in artificial intelligence and robotics, which can effectively improve the intelligence of real-world agents (i.e. robots) serving hu…
Ensemble Semi-supervised Entity Alignment via Cycle-teaching
Kexuan Xin, Zequn Sun, Wen Hua +4
Entity alignment is to find identical entities in different knowledge graphs. Although embedding-based entity alignment has recently achieved remarkable progress, training data ins…
Informed Multi-context Entity Alignment
Kexuan Xin, Zequn Sun, Wen Hua +2
Entity alignment is a crucial step in integrating knowledge graphs (KGs) from multiple sources. Previous attempts at entity alignment have explored different KG structures, such as…