85 citations · 113 across the 6 of their papers we have counts for
10 papers
Crowdsourcing on Sensitive Data with Privacy-Preserving Text Rewriting
Nina Mouhammad, Johannes Daxenberger, Benjamin Schiller +1
Most tasks in NLP require labeled data. Data labeling is often done on crowdsourcing platforms due to scalability reasons. However, publishing data on public platforms can only be…
Augmented SBERT: Data Augmentation Method for Improving Bi-Encoders for Pairwise Sentence Scoring Tasks
Nandan Thakur, Nils Reimers, Johannes Daxenberger +1
There are two approaches for pairwise sentence scoring: Cross-encoders, which perform full-attention over the input pair, and Bi-encoders, which map each input independently to a d…
Aspect-Controlled Neural Argument Generation
Benjamin Schiller, Johannes Daxenberger, Iryna Gurevych
We rely on arguments in our daily lives to deliver our opinions and base them on evidence, making them more convincing in turn. However, finding and formulating arguments can be ch…
Stance Detection Benchmark: How Robust Is Your Stance Detection?
Benjamin Schiller, Johannes Daxenberger, Iryna Gurevych
Stance Detection (StD) aims to detect an author's stance towards a certain topic or claim and has become a key component in applications like fake news detection, claim validation,…
Classification and Clustering of Arguments with Contextualized Word Embeddings
Nils Reimers, Benjamin Schiller, Tilman Beck +3
We experiment with two recent contextualized word embedding methods (ELMo and BERT) in the context of open-domain argument search. For the first time, we show how to leverage the p…
Fine-Grained Argument Unit Recognition and Classification
Dietrich Trautmann, Johannes Daxenberger, Christian Stab +2
Prior work has commonly defined argument retrieval from heterogeneous document collections as a sentence-level classification task. Consequently, argument retrieval suffers both fr…
Cross-lingual Argumentation Mining: Machine Translation (and a bit of Projection) is All You Need!
Steffen Eger, Johannes Daxenberger, Christian Stab +1
Argumentation mining (AM) requires the identification of complex discourse structures and has lately been applied with success monolingually. In this work, we show that the existin…
Multi-Task Learning for Argumentation Mining in Low-Resource Settings
Claudia Schulz, Steffen Eger, Johannes Daxenberger +2
We investigate whether and where multi-task learning (MTL) can improve performance on NLP problems related to argumentation mining (AM), in particular argument component identifica…
Neural End-to-End Learning for Computational Argumentation Mining
Steffen Eger, Johannes Daxenberger, Iryna Gurevych
We investigate neural techniques for end-to-end computational argumentation mining (AM). We frame AM both as a token-based dependency parsing and as a token-based sequence tagging…
What is the Essence of a Claim? Cross-Domain Claim Identification
Johannes Daxenberger, Steffen Eger, Ivan Habernal +2
Argument mining has become a popular research area in NLP. It typically includes the identification of argumentative components, e.g. claims, as the central component of an argumen…