Papers by Matei Bejan

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Challenge:	Methods for Anomaly Detection in text have shown strong empirical results on ad-hoc anomaly setups that are usually made by downsampling some classes of a labeled dataset.
Approach:	They propose a unified benchmark for detecting various types of anomalies . they evaluate two strong shallow baselines and two current state-of-the-art neural approaches .
Outcome:	The proposed benchmarks provide insights into the knowledge the neural models are learning when performing the task.