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Hate Speech Detection

Hate speech detection is the task of detecting if communication such as text, audio, and so on contains hatred and or encourages violence towards a person or a group of people. This is usually based on prejudice against 'protected characteristics' such as their ethnicity, gender, sexual orientation, religion, age et al. Some example benchmarks are ETHOS and HateXplain. Models can be evaluated with metrics like the F-score or F-measure.

Papers

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Showing 1–50 of 507 papers

TitleStatusHype
Fine-Grained Chinese Hate Speech Understanding: Span-Level Resources, Coded Term Lexicon, and Enhanced Detection Frameworks—0
Rethinking Hate Speech Detection on Social Media: Can LLMs Replace Traditional Models?—0
Towards Fairness Assessment of Dutch Hate Speech Detection—0
ToxSyn-PT: A Large-Scale Synthetic Dataset for Hate Speech Detection in Portuguese—0
Hateful Person or Hateful Model? Investigating the Role of Personas in Hate Speech Detection by Large Language Models—0
Multilingual Hate Speech Detection in Social Media Using Translation-Based Approaches with Large Language Models—0
Cracking the Code: Enhancing Implicit Hate Speech Detection through Coding Classification—0
On Fairness of Task Arithmetic: The Role of Task Vectors—0
AmpleHate: Amplifying the Attention for Versatile Implicit Hate DetectionCode0
Social Good or Scientific Curiosity? Uncovering the Research Framing Behind NLP Artefacts—0
All You Need is "Leet": Evading Hate-speech Detection AICode0
Data-Efficient Hate Speech Detection via Cross-Lingual Nearest Neighbor Retrieval with Limited Labeled Data—0
Can Prompting LLMs Unlock Hate Speech Detection across Languages? A Zero-shot and Few-shot Study—0
Exploring new Approaches for Information Retrieval through Natural Language Processing—0
Personalisation or Prejudice? Addressing Geographic Bias in Hate Speech Detection using Debias Tuning in Large Language ModelsCode0
Towards High-Fidelity Synthetic Multi-platform Social Media Datasets via Large Language Models—0
Few-shot Hate Speech Detection Based on the MindSpore Framework—0
Selective Demonstration Retrieval for Improved Implicit Hate Speech Detection—0
BOISHOMMO: Holistic Approach for Bangla Hate Speech—0
Improving Hate Speech Classification with Cross-Taxonomy Dataset IntegrationCode0
Evaluation of Hate Speech Detection Using Large Language Models and Geographical ContextualizationCode0
Sarang at DEFACTIFY 4.0: Detecting AI-Generated Text Using Noised Data and an Ensemble of DeBERTa Models—0
Subjective Logic EncodingsCode0
Code-Mixed Telugu-English Hate Speech Detection—0
Towards a Robust Framework for Multimodal Hate Detection: A Study on Video vs. Image-based ContentCode0
The Impact of Persona-based Political Perspectives on Hateful Content Detection—0
HateBench: Benchmarking Hate Speech Detectors on LLM-Generated Content and Hate CampaignsCode1
STATE ToxiCN: A Benchmark for Span-level Target-Aware Toxicity Extraction in Chinese Hate Speech DetectionCode1
Evaluating Simple Debiasing Techniques in RoBERTa-based Hate Speech Detection Models—0
Cross-Modal Transfer from Memes to Videos: Addressing Data Scarcity in Hateful Video DetectionCode0
Digital Guardians: Can GPT-4, Perspective API, and Moderation API reliably detect hate speech in reader comments of German online newspapers?—0
SAFE-MEME: Structured Reasoning Framework for Robust Hate Speech Detection in MemesCode0
IITR-CIOL@NLU of Devanagari Script Languages 2025: Multilingual Hate Speech Detection and Target Identification in Devanagari-Scripted Languages—0
LLMsAgainstHate @ NLU of Devanagari Script Languages 2025: Hate Speech Detection and Target Identification in Devanagari Languages via Parameter Efficient Fine-Tuning of LLMsCode0
SubData: Bridging Heterogeneous Datasets to Enable Theory-Driven Evaluation of Political and Demographic Perspectives in LLMs—0
Towards Efficient and Explainable Hate Speech Detection via Model DistillationCode0
Common Ground, Diverse Roots: The Difficulty of Classifying Common Examples in Spanish Varieties—0
Navigating Dialectal Bias and Ethical Complexities in Levantine Arabic Hate Speech Detection—0
NLPineers@ NLU of Devanagari Script Languages 2025: Hate Speech Detection using Ensembling of BERT-based modelsCode0
A Federated Approach to Few-Shot Hate Speech Detection for Marginalized Communities—0
Multi-Granularity Tibetan Textual Adversarial Attack Method Based on Masked Language ModelCode0
A Survey on Automatic Online Hate Speech Detection in Low-Resource Languages—0
On Importance of Code-Mixed Embeddings for Hate Speech Identification—0
BERT or FastText? A Comparative Analysis of Contextual as well as Non-Contextual EmbeddingsCode0
On Limitations of LLM as Annotator for Low Resource Languages—0
BanglaEmbed: Efficient Sentence Embedding Models for a Low-Resource Language Using Cross-Lingual Distillation Techniques—0
The Promises and Pitfalls of LLM Annotations in Dataset Labeling: a Case Study on Media Bias DetectionCode0
Gender Bias Mitigation for Bangla Classification TasksCode0
A Unified Multi-Task Learning Architecture for Hate Detection Leveraging User-Based Information—0
Untangling Hate Speech Definitions: A Semantic Componential Analysis Across Cultures and Domains—0
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All datasetsEthos BinaryHateXplainEthos MultiLabelWaseem et al., 2018AbusEvalAutomatic Misogynistic IdentificationHateMMHatEvalOffensEval 2019ToLD-Brbajer_danish_misogynyDKhate

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1BiLSTM + static BEF1-score0.8—Unverified
2BERTF1-score0.79—Unverified
3BiLSTM+Attention+FTF1-score0.77—Unverified
4OPT-175B (few-shot)F1-score0.76—Unverified
5CNN+Attention+FT+GVF1-score0.74—Unverified
6OPT-175B (one-shot)F1-score0.71—Unverified
7OPT-175B (zero-shot)F1-score0.67—Unverified
8SVMF1-score0.66—Unverified
9Random ForestsF1-score0.64—Unverified
10Davinci (zero-shot)F1-score0.63—Unverified
#ModelMetricClaimedVerifiedStatus
1BERT-MRPAUROC0.86—Unverified
2BERT-RPAUROC0.85—Unverified
3BERT-HateXplain [Attn]AUROC0.85—Unverified
4BERT-HateXplain [LIME]AUROC0.85—Unverified
5BERT [Attn]AUROC0.84—Unverified
6BiRNN-HateXplain [Attn]AUROC0.81—Unverified
7BiRNN-Attn [Attn]AUROC0.8—Unverified
8CNN-GRU [LIME]AUROC0.79—Unverified
9BiRNN [LIME]AUROC0.77—Unverified
10XG-HSI-BERTAccuracy0.75—Unverified
#ModelMetricClaimedVerifiedStatus
1MLARAMHamming Loss0.29—Unverified
2MLkNNHamming Loss0.16—Unverified
3Binary RelevanceHamming Loss0.14—Unverified
4Neural Classifier ChainsHamming Loss0.13—Unverified
5Neural Binary RelevanceHamming Loss0.11—Unverified
#ModelMetricClaimedVerifiedStatus
1Mozafari et al., 2019AAA50.94—Unverified
2SVMAAA46.51—Unverified
3Kennedy et al., 2020AAA45.5—Unverified
#ModelMetricClaimedVerifiedStatus
1HateBERTMacro F10.74—Unverified
2BERTMacro F10.72—Unverified
#ModelMetricClaimedVerifiedStatus
1mBertAccuracy0.83—Unverified
2Logistic RegressionAccuracy0.7—Unverified
#ModelMetricClaimedVerifiedStatus
1HXP + CLAP + CLIPTEST F1 (macro)0.85—Unverified
2BERT + ViT + MFCCTEST F1 (macro)0.79—Unverified
#ModelMetricClaimedVerifiedStatus
1HateBERTMacro F10.49—Unverified
2BERTMacro F10.48—Unverified
#ModelMetricClaimedVerifiedStatus
1HateBERTMacro F10.81—Unverified
2BERTMacro F10.8—Unverified
#ModelMetricClaimedVerifiedStatus
1Multilingual BERTF1-score0.75—Unverified
2AutoMLF1-score0.74—Unverified
#ModelMetricClaimedVerifiedStatus
1AOM mBERTF10.85—Unverified
#ModelMetricClaimedVerifiedStatus
1BaselineF10.7—Unverified
#ModelMetricClaimedVerifiedStatus
1RoBERTa-large-STMacro F180.7—Unverified
#ModelMetricClaimedVerifiedStatus
1Baseline BERT (task A)F10.77—Unverified