Papers Abuse Detection
“Abuse Detection” 태그가 달린 논문 73편 · 필터 해제
Creating and Evaluating Code-Mixed Nepali-English and Telugu-English Datasets for Abusive Language Detection Using Traditional and Deep Learning Models
With the growing presence of multilingual users on social media, detecting abusive language in code-mixed text has become increasingly challenging. Code-mixed communication, where users seamlessly switch between English …
Abuse DetectionAbusive LanguagePredictive Response Optimization: Using Reinforcement Learning to Fight Online Social Network Abuse
Detecting phishing, spam, fake accounts, data scraping, and other malicious activity in online social networks (OSNs) is a problem that has been studied for well over a decade, with a number of important results. Nearly …
Abuse DetectionA survey of textual cyber abuse detection using cutting-edge language models and large language models
The success of social media platforms has facilitated the emergence of various forms of online abuse within digital communities. This abuse manifests in multiple ways, including hate speech, cyberbullying, emotional abus…
Abuse DetectionEthicsHP-BERT: A framework for longitudinal study of Hinduphobia on social media via LLMs
During the COVID-19 pandemic, community tensions intensified, fuelling Hinduphobic sentiments and discrimination against individuals of Hindu descent within India and worldwide. Large language models (LLMs) have become p…
Abuse DetectionMisinformationSentiment AnalysisTowards Cross-Lingual Audio Abuse Detection in Low-Resource Settings with Few-Shot Learning
Online abusive content detection, particularly in low-resource settings and within the audio modality, remains underexplored. We investigate the potential of pre-trained audio representations for detecting abusive langua…
Abuse DetectionAbusive LanguageFew-Shot LearningMeta-LearningDetoxBench: Benchmarking Large Language Models for Multitask Fraud & Abuse Detection
Large language models (LLMs) have demonstrated remarkable capabilities in natural language processing tasks. However, their practical application in high-stake domains, such as fraud and abuse detection, remains an area …
Abuse DetectionAbusive LanguageBenchmarkingFraud Detection+1CoLLAB: A Collaborative Approach for Multilingual Abuse Detection
In this study, we investigate representations from paralingual Pre-Trained model (PTM) for Audio Abuse Detection (AAD), which has not been explored for AAD. Our results demonstrate their superiority compared to other PTM…
Abuse DetectionBreaking the Silence Detecting and Mitigating Gendered Abuse in Hindi, Tamil, and Indian English Online Spaces
Online gender-based harassment is a widespread issue limiting the free expression and participation of women and marginalized genders in digital spaces. Detecting such abusive content can enable platforms to curb this me…
Abuse DetectionAbusive LanguageWord EmbeddingsOverview of the 2023 ICON Shared Task on Gendered Abuse Detection in Indic Languages
This paper reports the findings of the ICON 2023 on Gendered Abuse Detection in Indic Languages. The shared task deals with the detection of gendered abuse in online text. The shared task was conducted as a part of ICON …
Abuse DetectionVoucher Abuse Detection with Prompt-based Fine-tuning on Graph Neural Networks
Voucher abuse detection is an important anomaly detection problem in E-commerce. While many GNN-based solutions have emerged, the supervised paradigm depends on a large quantity of labeled data. A popular alternative is …
Abuse DetectionAnomaly DetectionDetection of Children Abuse by Voice and Audio Classification by Short-Time Fourier Transform Machine Learning implemented on Nvidia Edge GPU device
The safety of children in children home has become an increasing social concern, and the purpose of this experiment is to use machine learning applied to detect the scenarios of child abuse to increase the safety of chil…
Abuse DetectionAudio ClassificationGPUimage-classification+1TCAB: A Large-Scale Text Classification Attack Benchmark
We introduce the Text Classification Attack Benchmark (TCAB), a dataset for analyzing, understanding, detecting, and labeling adversarial attacks against text classifiers. TCAB includes 1.5 million attack instances, gene…
Abuse DetectionClassificationSentiment Analysistext-classification+1Machine Generated Text: A Comprehensive Survey of Threat Models and Detection Methods
Machine generated text is increasingly difficult to distinguish from human authored text. Powerful open-source models are freely available, and user-friendly tools that democratize access to generative models are prolife…
Abuse DetectionFairnessSurveyText Detection+1Explainable Abuse Detection as Intent Classification and Slot Filling
To proactively offer social media users a safe online experience, there is a need for systems that can detect harmful posts and promptly alert platform moderators. In order to guarantee the enforcement of a consistent po…
Abuse DetectionGeneral Classificationintent-classificationIntent Classification+1Adversarial Robustness for Tabular Data through Cost and Utility Awareness
Many safety-critical applications of machine learning, such as fraud or abuse detection, use data in tabular domains. Adversarial examples can be particularly damaging for these applications. Yet, existing works on adver…
Abuse DetectionAdversarial RobustnessEnriching Abusive Language Detection with Community Context
Uses of pejorative expressions can be benign or actively empowering. When models for abuse detection misclassify these expressions as derogatory, they inadvertently censor productive conversations held by marginalized gr…
Abuse DetectionAbusive LanguageDarkness can not drive out darkness: Investigating Bias in Hate SpeechDetection Models
It has become crucial to develop tools for automated hate speech and abuse detection. These tools would help to stop the bullies and the haters and provide a safer environment for individuals especially from marginalized…
Abuse DetectionHate Speech DetectionDE-ABUSE@TamilNLP-ACL 2022: Transliteration as Data Augmentation for Abuse Detection in Tamil
With the rise of social media and internet, thereis a necessity to provide an inclusive space andprevent the abusive topics against any gender,race or community. This paper describes thesystem submitted to the ACL-2022 s…
Abuse DetectionData AugmentationTransliterationImproving Generalizability in Implicitly Abusive Language Detection with Concept Activation Vectors
Robustness of machine learning models on ever-changing real-world data is critical, especially for applications affecting human well-being such as content moderation. New kinds of abusive language continually emerge in o…
Abuse DetectionAbusive LanguageMultilingual and Multimodal Abuse Detection
The presence of abusive content on social media platforms is undesirable as it severely impedes healthy and safe social media interactions. While automatic abuse detection has been widely explored in textual domain, audi…
Abuse Detection