1 citations · 2 across the 4 of their papers we have counts for
6 papers
Beyond a Single Perspective: Text Anomaly Detection with Multi-View Language Representations
Yixin Liu, Kehan Yan, Shiyuan Li +2
Text anomaly detection (TAD) plays a critical role in various language-driven real-world applications, including harmful content moderation, phishing detection, and spam review fil…
OFA-MAS: One-for-All Multi-Agent System Topology Design based on Mixture-of-Experts Graph Generative Models
Shiyuan Li, Yixin Liu, Yu Zheng +3
Multi-Agent Systems (MAS) offer a powerful paradigm for solving complex problems, yet their performance is critically dependent on the design of their underlying collaboration topo…
Graph-Augmented Large Language Model Agents: Current Progress and Future Prospects
Yixin Liu, Guibin Zhang, Kun Wang +2
Autonomous agents based on large language models (LLMs) have demonstrated impressive capabilities in a wide range of applications, including web navigation, software development, a…
FreeGAD: A Training-Free yet Effective Approach for Graph Anomaly Detection
Yunfeng Zhao, Yixin Liu, Shiyuan Li +3
Graph Anomaly Detection (GAD) aims to identify nodes that deviate from the majority within a graph, playing a crucial role in applications such as social networks and e-commerce. D…
Assemble Your Crew: Automatic Multi-agent Communication Topology Design via Autoregressive Graph Generation
Shiyuan Li, Yixin Liu, Qingsong Wen +2
Multi-agent systems (MAS) based on large language models (LLMs) have emerged as a powerful solution for dealing with complex problems across diverse domains. The effectiveness of M…
Uncertainty-Aware Graph Neural Networks: A Multi-Hop Evidence Fusion Approach
Qingfeng Chen, Shiyuan Li, Yixin Liu +3
Graph neural networks (GNNs) excel in graph representation learning by integrating graph structure and node features. Existing GNNs, unfortunately, fail to account for the uncertai…