Toxic Spans Detection
17 papers with code • 0 benchmarks • 1 datasets
Given a sentence identify the toxic spans present in it.
Benchmarks
These leaderboards are used to track progress in Toxic Spans Detection
CAD
Most implemented papers
YNU-HPCC at SemEval-2021 Task 5: Using a Transformer-based Model with Auxiliary Information for Toxic Span Detection
chenrj233/semeval2021_task5
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SEMEVAL 2021
In this paper, a transformer-based model with auxiliary information is proposed for SemEval-2021 Task 5.
Sefamerve ARGE at SemEval-2021 Task 5: Toxic Spans Detection Using Segmentation Based 1-D Convolutional Neural Network Model
birolkuyumcu/wawunet_for_toxicspan
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SEMEVAL 2021
This paper describes our contribution to SemEval-2021 Task 5: Toxic Spans Detection.
Entity at SemEval-2021 Task 5: Weakly Supervised Token Labelling for Toxic Spans Detection
The baseline approach for this problem using the transformer model is to add a token classification head to the language model and fine-tune the layers with the token labeled dataset.
YoungSheldon at SemEval-2021 Task 5: Fine-tuning Pre-trained Language Models for Toxic Spans Detection using Token classification Objective
In this paper, we describe our system used for SemEval 2021 Task 5: Toxic Spans Detection.
UoB at SemEval-2021 Task 5: Extending Pre-Trained Language Models to Include Task and Domain-Specific Information for Toxic Span Prediction
erikdyan/toxic_span_detection
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SEMEVAL 2021
Toxicity is pervasive in social media and poses a major threat to the health of online communities.
Cross-Domain Toxic Spans Detection
Given the dynamic nature of toxic language use, automated methods for detecting toxic spans are likely to encounter distributional shift.
