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Found 6 papers, 1 papers with code
Amsqr at SemEval-2022 Task 4: Towards AutoNLP via Meta-Learning and Adversarial Data Augmentation for PCL Detection
This paper describes the use of AutoNLP techniques applied to the detection of patronizing and condescending language (PCL) in a binary classification scenario.
Tackling Data Drift with Adversarial Validation: An Application for German Text Complexity Estimation
This paper describes the winning approach in the first automated German text complexity assessment shared task as part of KONVENS 2022.
Alejandro Mosquera at SemEval-2021 Task 1: Exploring Sentence and Word Features for Lexical Complexity Prediction
This paper revisits feature engineering approaches for predicting the complexity level of English words in a particular context using regression techniques.
Amsqr at SemEval-2020 Task 12: Offensive Language Detection Using Neural Networks and Anti-adversarial Features
This paper describes a method and system to solve the problem of detecting offensive language in social media using anti-adversarial features.
Detecting DGA domains with recurrent neural networks and side information
Our experiments show the model is capable of effectively identifying domains generated by difficult DGA families.
On Detecting Messaging Abuse in Short Text Messages using Linguistic and Behavioral patterns
The use of short text messages in social media and instant messaging has become a popular communication channel during the last years.
