arXiv:2506.14933
공식 코드 · Papers with Code
Explain First, Trust Later: LLM-Augmented Explanations for Graph-Based Crypto Anomaly Detection
원문 초록
The decentralized finance (DeFi) community has grown rapidly in recent years, pushed forward by cryptocurrency enthusiasts interested in the vast untapped potential of new markets. The surge in popularity of cryptocurrency has ushered in a new era of financial crime. Unfortunately, the novelty of the technology makes the task of catching and prosecuting offenders particularly challenging. Thus, it is necessary to implement automated detection tools related to policies to address the growing criminality in the cryptocurrency realm.
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Towards High-Resolution 3D Anomaly Detection: A Scalable Dataset and Real-Time Framework for Subtle Industrial Defects
Evaluating Language Models For Threat Detection in IoT Security Logs
mTSBench: Benchmarking Multivariate Time Series Anomaly Detection and Model Selection at Scale
Benchmarking Unsupervised Strategies for Anomaly Detection in Multivariate Time Series
E-ABIN: an Explainable module for Anomaly detection in BIological Networks
Exact Matrix Seriation through Mathematical Optimization: Stress and Effectiveness-Based Models
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