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ORCIDGermEval@KONVENS 2021: Düsseldorf, Germany
- Julian Risch, Anke Stoll, Lena Wilms, Michael Wiegand:
Proceedings of the GermEval 2021 Shared Task on the Identification of Toxic, Engaging, and Fact-Claiming Comments, GermEval@KONVENS 2021, Düsseldorf, Germany, September 6, 2021. Association for Computational Linguistics 2021 - Frontmatter.
- Julian Risch, Anke Stoll, Lena Wilms, Michael Wiegand
:
Overview of the GermEval 2021 Shared Task on the Identification of Toxic, Engaging, and Fact-Claiming Comments. 1-12 - Robin Schaefer, Manfred Stede:
UPAppliedCL at GermEval 2021: Identifying Fact-Claiming and Engaging Facebook Comments Using Transformers. 13-18 - Christian Gawron, Sebastian Schmidt:
FH-SWF SG at GermEval 2021: Using Transformer-Based Language Models to Identify Toxic, Engaging, & Fact-Claiming Comments. 19-24 - Rémi Calizzano, Malte Ostendorff, Georg Rehm:
DFKI SLT at GermEval 2021: Multilingual Pre-training and Data Augmentation for the Classification of Toxicity in Social Media Comments. 25-31 - Skye Morgan, Tharindu Ranasinghe, Marcos Zampieri:
WLV-RIT at GermEval 2021: Multitask Learning with Transformers to Detect Toxic, Engaging, and Fact-Claiming Comments. 32-38 - T. H. Arjun, Arvindh A., Ponnurangam Kumaraguru:
Precog-LTRC-IIITH at GermEval 2021: Ensembling Pre-Trained Language Models with Feature Engineering. 39-46 - Fabian Haak, Björn Engelmann:
IRCologne at GermEval 2021: Toxicity Classification. 47-53 - Mina Schütz, Christoph Demus, Jonas Pitz, Nadine Probol, Melanie Siegel, Dirk Labudde:
DeTox at GermEval 2021: Toxic Comment Classification. 54-61 - Maximilian Schmidhuber:
Universität Regensburg MaxS at GermEval 2021 Task 1: Synthetic Data in Toxic Comment Classification. 62-68 - Kinga Gémes, Gábor Recski:
TUW-Inf at GermEval2021: Rule-based and Hybrid Methods for Detecting Toxic, Engaging, and Fact-Claiming Comments. 69-75 - Jaqueline Böck, Daria Liakhovets, Mina Schütz, Armin Kirchknopf, Djordje Slijepcevic, Matthias Zeppelzauer, Alexander Schindler:
AIT_FHSTP at GermEval 2021: Automatic Fact Claiming Detection with Multilingual Transformer Models. 76-82 - Hoai Nam Tran, Udo Kruschwitz:
ur-iw-hnt at GermEval 2021: An Ensembling Strategy with Multiple BERT Models. 83-87 - Niclas Hildebrandt, Benedikt T. Boenninghoff, Dennis Orth, Christopher Schymura:
Data Science Kitchen at GermEval 2021: A Fine Selection of Hand-Picked Features, Delivered Fresh from the Oven. 88-94 - Kwabena Odame Akomeah, Udo Kruschwitz, Bernd Ludwig:
UR@NLP_A_Team @ GermEval 2021: Ensemble-based Classification of Toxic, Engaging and Fact-Claiming Comments. 95-99 - Subhadarshi Panda, Sarah Ita Levitan:
HunterSpeechLab at GermEval 2021: Does Your Comment Claim A Fact? Contextualized Embeddings for German Fact-Claiming Comment Classification. 100-104 - Tobias Bornheim, Niklas Grieger, Stephan Bialonski:
FHAC at GermEval 2021: Identifying German toxic, engaging, and fact-claiming comments with ensemble learning. 105-111
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