Search Results for author:
Found 4 papers, 3 papers with code
VeriDark: A Large-Scale Benchmark for Authorship Verification on the Dark Web
The DarkWeb represents a hotbed for illicit activity, where users communicate on different market forums in order to exchange goods and services.
AnoShift: A Distribution Shift Benchmark for Unsupervised Anomaly Detection
Analyzing the distribution shift of data is a growing research direction in nowadays Machine Learning (ML), leading to emerging new benchmarks that focus on providing a suitable scenario for studying the generalization properties of ML models.
Ranked #1 on
Unsupervised Anomaly Detection
on AnoShift
Rethinking the Authorship Verification Experimental Setups
One of the main drivers of the recent advances in authorship verification is the PAN large-scale authorship dataset.
DATE: Detecting Anomalies in Text via Self-Supervision of Transformers
Leveraging deep learning models for Anomaly Detection (AD) has seen widespread use in recent years due to superior performances over traditional methods.
Ranked #1 on
Anomaly Detection
on AG News
