Search Results for author:
Found 13 papers, 7 papers with code
Adversarial Authorship Attribution for Deobfuscation
Our results motivate the need to develop authorship obfuscation approaches that are resistant to deobfuscation.
Don’t sweat the small stuff, classify the rest: Sample Shielding to protect text classifiers against adversarial attacks
Deep learning (DL) is being used extensively for text classification.
Style Matters! Investigating Linguistic Style in Online Communities
Content has historically been the primary lens used to study language in online communities.
Smells like Teen Spirit: An Exploration of Sensorial Style in Literary Genres
For example, we observe that 4 of the top 6 representative features in novels collection involved individuals using olfactory language where we expected them to use non-olfactory language.
Don't sweat the small stuff, classify the rest: Sample Shielding to protect text classifiers against adversarial attacks
Deep learning (DL) is being used extensively for text classification.
A Girl Has A Name, And It's ... Adversarial Authorship Attribution for Deobfuscation
Specifically, they are not evaluated against adversarially trained authorship attributors that are aware of potential obfuscation.
Suum Cuique: Studying Bias in Taboo Detection with a Community Perspective
In essence, these classifiers represent community level language norms.
On The Robustness of Offensive Language Classifiers
Social media platforms are deploying machine learning based offensive language classification systems to combat hateful, racist, and other forms of offensive speech at scale.
Avengers Ensemble! Improving Transferability of Authorship Obfuscation
Our experiments show that if an obfuscator can evade an ensemble attribution classifier, which is based on multiple base attribution classifiers, it is more likely to transfer to different attribution classifiers.
Through the Looking Glass: Learning to Attribute Synthetic Text Generated by Language Models
Given the potential misuse of recent advances in synthetic text generation by language models (LMs), it is important to have the capacity to attribute authorship of synthetic text.
A Girl Has A Name: Detecting Authorship Obfuscation
Authorship attribution aims to identify the author of a text based on the stylometric analysis.
NLP@UIOWA at SemEval-2019 Task 6: Classifying the Crass using Multi-windowed CNNs
This paper proposes a system for OffensEval (SemEval 2019 Task 6), which calls for a system to classify offensive language into several categories.
