FH-SWF SG at GermEval 2021: Using Transformer-Based Language Models to Identify Toxic, Engaging, & Fact-Claiming Comments

7 September 2021

Papers citing "FH-SWF SG at GermEval 2021: Using Transformer-Based Language Models to Identify Toxic, Engaging, & Fact-Claiming Comments"

5 / 5 papers shown

Title
Assessing In-context Learning and Fine-tuning for Topic Classification of German Web Data Julian Schelb Roberto Ulloa Andreas Spitz 36 3 0 23 Jul 2024
POLygraph: Polish Fake News Dataset Daniel Dzienisiewicz Filip Graliñski Piotr Jabłoński Marek Kubis Paweł Skórzewski Piotr Wierzchoñ 42 0 0 01 Jul 2024
LCT-1 at SemEval-2023 Task 10: Pre-training and Multi-task Learning for Sexism Detection and Classification K. Chernyshev E. Garanina Duygu Bayram Qiankun Zheng Lukas Edman 13 0 0 08 Jun 2023
Automatic Readability Assessment of German Sentences with Transformer Ensembles Patrick Gustav Blaneck Tobias Bornheim Niklas Grieger Stephan Bialonski 54 10 0 09 Sep 2022
What the [MASK]? Making Sense of Language-Specific BERT Models Debora Nozza Federico Bianchi Dirk Hovy 92 106 0 05 Mar 2020