122 citations · 146 across the 6 of their papers we have counts for
12 papers
Application of the interactive Leipzig Corpus Miner as a generic research platform for the use in the social sciences
Christian Kahmann, Andreas Niekler, Gregor Wiedemann
This article introduces to the interactive Leipzig Corpus Miner (iLCM) - a newly released, open-source software to perform automatic content analysis. Since the iLCM is based on th…
UHH-LT at SemEval-2020 Task 12: Fine-Tuning of Pre-Trained Transformer Networks for Offensive Language Detection
Gregor Wiedemann, Seid Muhie Yimam, Chris Biemann
Fine-tuning of pre-trained transformer networks such as BERT yield state-of-the-art results for text classification tasks. Typically, fine-tuning is performed on task-specific trai…
Does BERT Make Any Sense? Interpretable Word Sense Disambiguation with Contextualized Embeddings
Gregor Wiedemann, Steffen Remus, Avi Chawla +1
Contextualized word embeddings (CWE) such as provided by ELMo (Peters et al., 2018), Flair NLP (Akbik et al., 2018), or BERT (Devlin et al., 2019) are a major recent innovation in…
Adversarial Learning of Privacy-Preserving Text Representations for De-Identification of Medical Records
Max Friedrich, Arne Köhn, Gregor Wiedemann +1
De-identification is the task of detecting protected health information (PHI) in medical text. It is a critical step in sanitizing electronic health records (EHRs) to be shared for…
Transfer Learning from LDA to BiLSTM-CNN for Offensive Language Detection in Twitter
Gregor Wiedemann, Eugen Ruppert, Raghav Jindal +1
We investigate different strategies for automatic offensive language classification on German Twitter data. For this, we employ a sequentially combined BiLSTM-CNN neural network. B…
microNER: A Micro-Service for German Named Entity Recognition based on BiLSTM-CRF
Gregor Wiedemann, Raghav Jindal, Chris Biemann
For named entity recognition (NER), bidirectional recurrent neural networks became the state-of-the-art technology in recent years. Competing approaches vary with respect to pre-tr…