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
Most implemented papers
NLRG at SemEval-2021 Task 5: Toxic Spans Detection Leveraging BERT-based Token Classification and Span Prediction Techniques
In our paper, we explore simple versions of both of these approaches and their performance on the task.
UniParma at SemEval-2021 Task 5: Toxic Spans Detection Using CharacterBERT and Bag-of-Words Model
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.
HLE-UPC at SemEval-2021 Task 5: Multi-Depth DistilBERT for Toxic Spans Detection
This paper presents our submission to SemEval-2021 Task 5: Toxic Spans Detection.
IITK@Detox at SemEval-2021 Task 5: Semi-Supervised Learning and Dice Loss for Toxic Spans Detection
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
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
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.
MIPT-NSU-UTMN at SemEval-2021 Task 5: Ensembling Learning with Pre-trained Language Models for Toxic Spans Detection
This paper describes our system for SemEval-2021 Task 5 on Toxic Spans Detection.
UTNLP at SemEval-2021 Task 5: A Comparative Analysis of Toxic Span Detection using Attention-based, Named Entity Recognition, and Ensemble Models
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.
UIT-ISE-NLP at SemEval-2021 Task 5: Toxic Spans Detection with BiLSTM-CRF and ToxicBERT Comment Classification
We present our works on SemEval-2021 Task 5 about Toxic Spans Detection.
Cisco at SemEval-2021 Task 5: What's Toxic?: Leveraging Transformers for Multiple Toxic Span Extraction from Online Comments
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.