Search Results for author: Benjamin Schiller

Found 9 papers, 6 papers with code

Focusing Knowledge-based Graph Argument Mining via Topic Modeling

no code implementations3 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.

Argument Mining Decision Making +1

Aspect-Controlled Neural Argument Generation

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.

Data Augmentation Language Modelling +1

Stance Detection Benchmark: How Robust Is Your Stance Detection?

1 code implementation6 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.

Fake News Detection Multi-Task Learning +1

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

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.

Entity Linking General Classification +1

A Retrospective Analysis of the Fake News Challenge Stance-Detection Task

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.

General Classification Stance Classification +1

A Retrospective Analysis of the Fake News Challenge Stance Detection Task

7 code implementations13 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.

General Classification Stance Classification +1

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