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UIT-ISE-NLP at SemEval-2021 Task 5: Toxic Spans Detection with BiLSTM-CRF and ToxicBERT Comment Classification

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arxiv 2104.10100 v4 pith:IRUMLJE7 submitted 2021-04-20 cs.CL

classification cs.CL
keywords toxicdetectionmodeltaskspansbilstm-crfclassificationidentifying
verification ladder T0 review T1 audit T2 compute T3 formal
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We present our works on SemEval-2021 Task 5 about Toxic Spans Detection. This task aims to build a model for identifying toxic words in whole posts. We use the BiLSTM-CRF model combining with ToxicBERT Classification to train the detection model for identifying toxic words in posts. Our model achieves 62.23% by F1-score on the Toxic Spans Detection task.

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  1. Enhancing LLM-based Hatred and Toxicity Detection with Meta-Toxic Knowledge Graph

    cs.CL 2024-12 conditional novelty 6.0 of 10

    MetaTox constructs a meta-toxic knowledge graph from toxic corpora and injects retrieved triplets into LLM prompts, improving toxicity detection and lowering false positives, especially out-of-domain.

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