Replication data hosted for the paper 'Are LLM-Enhanced GNNs Privacy-Safe?' by Jimmy Wen. The dataset likely contains graph-structured data used to evaluate privacy risks in hybrid LLM-GNN models. It was last updated on May 6, 2026.
Use Cases
- Replicate privacy experiments based on the described LLM-GNN framework
- Benchmark privacy leakage in graph-based machine learning models
- Evaluate the safety of integrating LLMs with GNN architectures
- Analyze graph data properties that influence privacy vulnerabilities
Strengths
- Data is directly tied to a specific research paper, providing clear context
- Last update timestamp is May 6, 2026, indicating recent availability
Limitations
- Description metadata is limited; actual data quality requires manual inspection after download
- Column-level documentation is absent; field semantics must be inferred after download
- Row count is unknown, which may limit suitability assessment
Provenance
- Source
- Harvard Dataverse
- Freshness
- Last updated 2026-05-06 03:13:32