An Explainable DistilBERT-BiLSTM-Attention Framework for Binary and Multi-Class Hate Speech Detection

arXiv:2609.28703 · cs.CL, cs.AI · Submitted 2026-09-23 · Read on arXiv

cs.CL, cs.AI

Submitted: 2026-09-23

Updated: 2026-09-23

Terminology

• Transformer — 26× in this paper · explained in 2 episodes
• Accuracy — 23× in this paper · explained in 1 episode
• Embeddings — 22× in this paper · explained in 2 episodes
• Benchmark — 13× in this paper · explained in 2 episodes
• Ablation — 7× in this paper · explained in 1 episode
• Generalization — 6× in this paper · explained in 13 episodes
• Ablation study — 5× in this paper · explained in 1 episode
• Explainability — 4× in this paper · explained in 3 episodes
• Interpretability — 4× in this paper · explained in 15 episodes
• Low-Resource Languages — 4× in this paper · explained in 4 episodes
• Robustness — 4× in this paper · explained in 5 episodes
• Attention Mechanism — 3× in this paper · explained in 3 episodes
• Contextual Understanding — 3× in this paper · explained in 2 episodes
• Fine-Tuning — 3× in this paper · explained in 5 episodes
• Transformer Models — 3× in this paper · explained in 2 episodes
• Bidirectional Long Short-Term Memory — 2× in this paper
• Core — 2× in this paper · explained in 2 episodes
• False Negative — 2× in this paper
• False Positive — 2× in this paper
• Feature Extraction — 2× in this paper · explained in 2 episodes
• Hybrid Model — 2× in this paper · explained in 2 episodes
• Semi-supervised Learning — 2× in this paper · explained in 4 episodes
• True Negative — 2× in this paper
• True Positive — 2× in this paper
• Accountability — 1× in this paper · explained in 2 episodes
• Adam — 1× in this paper · explained in 2 episodes
• AdamW Optimizer — 1× in this paper · explained in 1 episode
• Alignment — 1× in this paper · explained in 1 episode
• Hybrid Architectures — 1× in this paper · explained in 3 episodes
• Hybrid Models — 1× in this paper · explained in 2 episodes
• Local Interpretable Model-agnostic Explanations — 1× in this paper
• Loss Function — 1× in this paper · explained in 2 episodes
• Model-Agnostic — 1× in this paper · explained in 2 episodes
• Tokenization — 1× in this paper · explained in 2 episodes
• Transfer Learning — 1× in this paper · explained in 10 episodes
• Vector Representations — 1× in this paper · explained in 2 episodes

Sources

• DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lighter

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