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Abuse Detection
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Abuse detection is the task of identifying abusive behaviors, such as hate speech, offensive language, sexism and racism, in utterances from social media platforms (Source: https://arxiv.org/abs/1802.00385).
논문
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Rethinking Hate Speech Detection on Social Media: Can LLMs Replace Traditional Models?
Towards Fairness Assessment of Dutch Hate Speech Detection
ToxSyn-PT: A Large-Scale Synthetic Dataset for Hate Speech Detection in Portuguese
Hateful Person or Hateful Model? Investigating the Role of Personas in Hate Speech Detection by Large Language Models
Multilingual Hate Speech Detection in Social Media Using Translation-Based Approaches with Large Language Models
Cracking the Code: Enhancing Implicit Hate Speech Detection through Coding Classification
On Fairness of Task Arithmetic: The Role of Task Vectors
AmpleHate: Amplifying the Attention for Versatile Implicit Hate Detection
Social Good or Scientific Curiosity? Uncovering the Research Framing Behind NLP Artefacts
All You Need is "Leet": Evading Hate-speech Detection AI
Data-Efficient Hate Speech Detection via Cross-Lingual Nearest Neighbor Retrieval with Limited Labeled Data
Can Prompting LLMs Unlock Hate Speech Detection across Languages? A Zero-shot and Few-shot Study
Exploring new Approaches for Information Retrieval through Natural Language Processing
Personalisation or Prejudice? Addressing Geographic Bias in Hate Speech Detection using Debias Tuning in Large Language Models
Towards High-Fidelity Synthetic Multi-platform Social Media Datasets via Large Language Models
Optimism, Expectation, or Sarcasm? Multi-Class Hope Speech Detection in Spanish and English
Creating and Evaluating Code-Mixed Nepali-English and Telugu-English Datasets for Abusive Language Detection Using Traditional and Deep Learning Models
Few-shot Hate Speech Detection Based on the MindSpore Framework
Selective Demonstration Retrieval for Improved Implicit Hate Speech Detection
BOISHOMMO: Holistic Approach for Bangla Hate Speech
Improving Hate Speech Classification with Cross-Taxonomy Dataset Integration
Evaluation of Hate Speech Detection Using Large Language Models and Geographical Contextualization
Sarang at DEFACTIFY 4.0: Detecting AI-Generated Text Using Noised Data and an Ensemble of DeBERTa Models
Predictive Response Optimization: Using Reinforcement Learning to Fight Online Social Network Abuse
Subjective Logic Encodings
Code-Mixed Telugu-English Hate Speech Detection
Towards a Robust Framework for Multimodal Hate Detection: A Study on Video vs. Image-based Content
The Impact of Persona-based Political Perspectives on Hateful Content Detection
HateBench: Benchmarking Hate Speech Detectors on LLM-Generated Content and Hate Campaigns
Evaluating Simple Debiasing Techniques in RoBERTa-based Hate Speech Detection Models
Cross-Modal Transfer from Memes to Videos: Addressing Data Scarcity in Hateful Video Detection
STATE ToxiCN: A Benchmark for Span-level Target-Aware Toxicity Extraction in Chinese Hate Speech Detection
A survey of textual cyber abuse detection using cutting-edge language models and large language models
HP-BERT: A framework for longitudinal study of Hinduphobia on social media via LLMs
Digital Guardians: Can GPT-4, Perspective API, and Moderation API reliably detect hate speech in reader comments of German online newspapers?
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