SOTAVerified

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

Showing 3140 of 507 papers

TitleStatusHype
Deep Learning for Hate Speech Detection: A Comparative StudyCode1
Few-shot Learning with Multilingual Language ModelsCode1
Zero-shot hashtag segmentation for multilingual sentiment analysisCode1
Hate Speech Detection Based on Sentiment Knowledge SharingCode1
HONEST: Measuring Hurtful Sentence Completion in Language ModelsCode1
AraCOVID19-MFH: Arabic COVID-19 Multi-label Fake News and Hate Speech Detection DatasetCode1
Detecting Hate Speech with GPT-3Code1
A Large-scale Dataset for Hate Speech Detection on Vietnamese Social Media TextsCode1
Learning from the Worst: Dynamically Generated Datasets to Improve Online Hate DetectionCode1
HateCheck: Functional Tests for Hate Speech Detection ModelsCode1
Show:102550
← PrevPage 4 of 51Next →

Benchmark Results

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