Toxic Spans Detection

17 papers with code • 0 benchmarks • 1 datasets

Given a sentence identify the toxic spans present in it.


Most implemented papers

UniParma at SemEval-2021 Task 5: Toxic Spans Detection Using CharacterBERT and Bag-of-Words Model

IMPLabUniPr/UniParma-at-semeval-2021-task-5 SEMEVAL 2021

We tackle this problem utilizing a combination of a state-of-the-art pre-trained language model (CharacterBERT) and a traditional bag-of-words technique.

IITK@Detox at SemEval-2021 Task 5: Semi-Supervised Learning and Dice Loss for Toxic Spans Detection

architb1703/Toxic_Span SEMEVAL 2021

In this work, we present our approach and findings for SemEval-2021 Task 5 - Toxic Spans Detection.

Lone Pine at SemEval-2021 Task 5: Fine-Grained Detection of Hate Speech Using BERToxic

Yakoob-Khan/Toxic-Spans-Detection SEMEVAL 2021

This paper describes our approach to the Toxic Spans Detection problem (SemEval-2021 Task 5).

WLV-RIT at SemEval-2021 Task 5: A Neural Transformer Framework for Detecting Toxic Spans

tharindudr/MUDES SEMEVAL 2021

In recent years, the widespread use of social media has led to an increase in the generation of toxic and offensive content on online platforms.

UTNLP at SemEval-2021 Task 5: A Comparative Analysis of Toxic Span Detection using Attention-based, Named Entity Recognition, and Ensemble Models

alirezasalemi7/SemEval2021-Toxic-Spans-Detection SEMEVAL 2021

Detecting which parts of a sentence contribute to that sentence's toxicity -- rather than providing a sentence-level verdict of hatefulness -- would increase the interpretability of models and allow human moderators to better understand the outputs of the system.

Cisco at SemEval-2021 Task 5: What's Toxic?: Leveraging Transformers for Multiple Toxic Span Extraction from Online Comments

Sreyan88/SemEval-2021-Toxic-Spans-Detection SEMEVAL 2021

We also explore a dependency parsing approach where we extract spans from the input sentence under the supervision of target span boundaries and rank our spans using a biaffine model.