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Towards the Early Detection of Child Predators in Chat Rooms: A BERT-based Approach ...
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To what extent do human explanations of model behavior align with actual model behavior? ...
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Elementary-Level Math Word Problem Generation using Pre-Trained Transformers ...
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What Models Know About Their Attackers: Deriving Attacker Information From Latent Representations ...
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The 2021 Conference on Empirical Methods in Natural Language Processing 2021; ., Adam; Asthana, Kalyani; Brophy, Jonathan; Hammoudeh, Zayd; Lowd, Daniel; Perkins, Carter; Reis, Sabrina; Singh, Sameer; Xie, Zhouhang; You, Wencong. - : Underline Science Inc., 2021
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Abstract:
Adversarial attacks curated against NLP models are increasingly becoming practical threats. Although various methods have been developed to detect adversarial attacks, securing learning-based NLP systems in practice would require more than identifying and evading perturbed instances. To address these issues, we propose a new set of adversary identification tasks, Attacker Attribute Classification via Textual Analysis (AACTA), that attempts to obtain more detailed information about the attackers from adversarial texts. Specifically, given a piece of adversarial text, we hope to accomplish tasks such as localizing perturbed tokens, identifying the attacker's access level to the target model, determining the evasion mechanism imposed, and specifying the perturbation type employed by the attacking algorithm. Our contributions are as follows: we formalize the task of classifying attacker attributes, and create a benchmark on various target models from sentiment classification and abuse detection domains. We show ...
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Keyword:
Computational Linguistics; Language Models; Machine Learning; Machine Learning and Data Mining; Natural Language Processing; Neural Network
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URL: https://dx.doi.org/10.48448/esp1-6t07
https://underline.io/lecture/39915-what-models-know-about-their-attackers-deriving-attacker-information-from-latent-representations
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Segment, Mask, and Predict: Augmenting Chinese Word Segmentation with Self-Supervision ...
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Coral: An Approach for Conversational Agents in Mental Health Applications ...
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#WhyDidTheyStay: An NLP-driven approach to analyzing the factors that affect domestic violence victims ...
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SciBERT-based Multitasking Deep Neural Architecture to identify Contribution Statements from Scientific articles ...
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"I don't know who she is": Discourse and Knowledge Driven Coreference Resolution ...
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Certified Robustness to Programmable Transformations in LSTMs ...
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Sinhala-English Code-mixed and Code-switched Data Classification ...
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Adverse Drug Reaction Classification of Tweets with Fusion of Text and Drug Representations ...
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Learning Cross-lingual Representations for Event Coreference Resolution with Multi-view Alignment and Optimal Transport ...
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VisualSem: a high-quality knowledge graph for vision and language ...
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Specializing Multilingual Language Models: An Empirical Study ...
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On the Language-specificity of Multilingual BERT and the Impact of Fine-tuning ...
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One-Shot Lexicon Learning for Low-Resource Machine Translation ...
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