activity
20182023
most citedA Retrospective Analysis of the Fake News Challenge Stance Detection Task

68 citations · 107 across the 6 of their papers we have counts for

collaborators

8 papers

cs.CL2023

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…

cs.IR2021★ 1 cited

Focusing Knowledge-based Graph Argument Mining via Topic Modeling

Patrick Abels, Zahra Ahmadi, Sophie Burkhardt +3

Decision-making usually takes five steps: identifying the problem, collecting data, extracting evidence, identifying pro and con arguments, and making decisions. Focusing on extrac…

cs.CL2020

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…

cs.CL2020

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,…

cs.CL2019★ 1 cited

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…

cs.IR2018★ 10 cited

UKP-Athene: Multi-Sentence Textual Entailment for Claim Verification

Andreas Hanselowski, Hao Zhang, Zile Li +4

The Fact Extraction and VERification (FEVER) shared task was launched to support the development of systems able to verify claims by extracting supporting or refuting facts from ra…