PumpSense provides a 280,000-post Telegram dataset with 2,246 labeled pumps and demonstrates BGE-M3 detection at F1 0.83 with 50ms latency plus LLM-based target extraction at 0.91 accuracy, outperforming rule-based methods.
Profit or deceit? mitigating pump and dump in defi via graph and contrastive learning
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Graph-based spatio-temporal models built from aggregated crypto market data detect pump-and-dump schemes more effectively than standard machine learning baselines.
citing papers explorer
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PumpSense: Real-Time Detection and Target Extraction of Crypto Pump-and-Dumps on Telegram
PumpSense provides a 280,000-post Telegram dataset with 2,246 labeled pumps and demonstrates BGE-M3 detection at F1 0.83 with 50ms latency plus LLM-based target extraction at 0.91 accuracy, outperforming rule-based methods.
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Fraud Detection in Cryptocurrency Markets with Spatio-Temporal Graph Neural Networks
Graph-based spatio-temporal models built from aggregated crypto market data detect pump-and-dump schemes more effectively than standard machine learning baselines.