no code implementations • NAACL 2018 • Christian Stab, Johannes Daxenberger, Chris Stahlhut, Tristan Miller, Benjamin Schiller, Christopher Tauchmann, Steffen Eger, Iryna Gurevych
Argument mining is a core technology for enabling argument search in large corpora.
7 code implementations • 13 Jun 2018 • Andreas Hanselowski, Avinesh PVS, Benjamin Schiller, Felix Caspelherr, Debanjan Chaudhuri, Christian M. Meyer, Iryna Gurevych
To date, there is no in-depth analysis paper to critically discuss FNC-1's experimental setup, reproduce the results, and draw conclusions for next-generation stance classification methods.
1 code implementation • COLING 2018 • Andreas Hanselowski, Avinesh PVS, Benjamin Schiller, Felix Caspelherr, Debanjan Chaudhuri, Christian M. Meyer, Iryna Gurevych
To date, there is no in-depth analysis paper to critically discuss FNC-1{'}s experimental setup, reproduce the results, and draw conclusions for next-generation stance classification methods.
1 code implementation • WS 2018 • Andreas Hanselowski, Hao Zhang, Zile Li, Daniil Sorokin, Benjamin Schiller, Claudia Schulz, Iryna Gurevych
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 raw text.
no code implementations • EMNLP 2018 • Christian Stab, Tristan Miller, Benjamin Schiller, Pranav Rai, Iryna Gurevych
Argument mining is a core technology for automating argument search in large document collections.
2 code implementations • ACL 2019 • Nils Reimers, Benjamin Schiller, Tilman Beck, Johannes Daxenberger, Christian Stab, Iryna Gurevych
We experiment with two recent contextualized word embedding methods (ELMo and BERT) in the context of open-domain argument search.
1 code implementation • 6 Jan 2020 • 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, and argument search.
1 code implementation • NAACL 2021 • Benjamin Schiller, Johannes Daxenberger, Iryna Gurevych
In this work, we train a language model for argument generation that can be controlled on a fine-grained level to generate sentence-level arguments for a given topic, stance, and aspect.
no code implementations • 3 Feb 2021 • Patrick Abels, Zahra Ahmadi, Sophie Burkhardt, Benjamin Schiller, Iryna Gurevych, Stefan Kramer
We use a topic model to extract topic- and sentence-specific evidence from the structured knowledge base Wikidata, building a graph based on the cosine similarity between the entity word vectors of Wikidata and the vector of the given sentence.
no code implementations • 23 May 2022 • Benjamin Schiller, Johannes Daxenberger, Iryna Gurevych
The task of Argument Mining, that is extracting argumentative sentences for a specific topic from large document sources, is an inherently difficult task for machine learning models and humans alike, as large Argument Mining datasets are rare and recognition of argumentative sentences requires expert knowledge.
no code implementations • 6 Mar 2023 • Nina Mouhammad, Johannes Daxenberger, Benjamin Schiller, Ivan Habernal
Most tasks in NLP require labeled data.