Population-Calibrated Graph Screening at 835-Million-Address Scale, with Label-Free Transfer to New Chains

arXiv:2609.03036 · cs.CR, cs.LG · Submitted 2026-09-02 · Read on arXiv

cs.CR, cs.LG

Submitted: 2026-09-02

Updated: 2026-09-02

Code: https://github.com/ai-decisions/openlabels

Terminology

• Provenance — 14× in this paper · explained in 3 episodes
• Embeddings — 11× in this paper · explained in 2 episodes
• Archetype — 9× in this paper · explained in 1 episode
• Calibration — 8× in this paper · explained in 7 episodes
• Ablation — 7× in this paper · explained in 1 episode
• Benchmark — 6× in this paper · explained in 2 episodes
• Clustering — 5× in this paper · explained in 2 episodes
• Degeneracy — 4× in this paper · explained in 3 episodes
• Transformer — 4× in this paper · explained in 2 episodes
• Aggregation — 3× in this paper · explained in 1 episode
• AUC — 2× in this paper · explained in 2 episodes
• Actor — 2× in this paper · explained in 3 episodes
• Consistency — 2× in this paper · explained in 3 episodes
• Heterogeneous Graph — 2× in this paper · explained in 2 episodes
• Knowledge Discovery and Data Mining — 2× in this paper
• Reinforcement Learning — 2× in this paper · explained in 4 episodes
• Representation Learning — 2× in this paper · explained in 2 episodes
• Sparsity — 2× in this paper · explained in 4 episodes
• Adam — 1× in this paper · explained in 2 episodes
• Adaptation — 1× in this paper · explained in 1 episode
• Data Provenance — 1× in this paper · explained in 2 episodes
• Deep Reinforcement Learning — 1× in this paper · explained in 2 episodes
• Failure Modes — 1× in this paper · explained in 3 episodes
• International Conference on Learning Representations — 1× in this paper
• Q-learning — 1× in this paper · explained in 3 episodes

Sources

• The Shape of Money Laundering: Subgraph Representation Learning on the Blockchain with the Elliptic2 Dataset
• Dota 2 with Large Scale Deep Reinforcement Learning
• Proximal Policy Optimization Algorithms
• Scalable Graph Learning for Anti-Money Laundering: A First Look
• Anti-Money Laundering in Bitcoin: Experimenting with Graph Convolutional Networks for Financial Forensics

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