6 papers
AgentRedBench: Dynamic Redteaming and Integration-Aware Defense for LLM Agents over SaaS Integrations
Hiskias Dingeto, William Leeney
Indirect prompt injection in tool-use agents is a concrete production threat: LLM agents read from integrations (third-party services such as Gmail, Salesforce, or Jira accessed th…
Non-Dissipative Graph Propagation for Non-Local Community Detection
William Leeney, Alessio Gravina, Davide Bacciu
Community detection in graphs aims to cluster nodes into meaningful groups, a task particularly challenging in heterophilic graphs, where nodes sharing similarities and membership…
Unsupervised Optimisation of GNNs for Node Clustering
William Leeney, Ryan McConville
Graph Neural Networks (GNNs) can be trained to detect communities within a graph by learning from the duality of feature and connectivity information. Currently, the common approac…
Uncertainty in GNN Learning Evaluations: A Comparison Between Measures for Quantifying Randomness in GNN Community Detection
William Leeney, Ryan McConville
(1) The enhanced capability of Graph Neural Networks (GNNs) in unsupervised community detection of clustered nodes is attributed to their capacity to encode both the connectivity a…
A Framework for Exploring Federated Community Detection
William Leeney, Ryan McConville
Federated Learning is machine learning in the context of a network of clients whilst maintaining data residency and/or privacy constraints. Community detection is the unsupervised…
Uncertainty in GNN Learning Evaluations: The Importance of a Consistent Benchmark for Community Detection
William Leeney, Ryan McConville
Graph Neural Networks (GNNs) have improved unsupervised community detection of clustered nodes due to their ability to encode the dual dimensionality of the connectivity and featur…