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Name: Maximilian Mozes
Type: User
Bio: PhD student at UCL. Interested in natural language processing.
Location: London, United Kingdom
Blog: http://mmozes.net
Name: Maximilian Mozes
Type: User
Bio: PhD student at UCL. Interested in natural language processing.
Location: London, United Kingdom
Blog: http://mmozes.net
Frequency-Guided Word Substitutions for Detecting Textual Adversarial Examples (EACL 2021)
Repository for the paper: van der Vegt, I., Mozes, M., Kleinberg, B. & Gill, P.(2020). The Grievance Dictionary: Understanding Threatening Language Use. Pre-print.
Contrasting Human- and Machine-Generated Word-Level Adversarial Examples for Text Classification (EMNLP 2021)
NETANOS: Named entity-based Text Anonymization for Open Science'
Code for Neural Motifs: Scene Graph Parsing with Global Context (CVPR 2018)
Must-read Papers on Textual Adversarial Attack and Defense
A Gentle Introduction to Word Embeddings for the Computational Social Sciences
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