5 papers by CopeNLU authors are accepted to appear at EMNLP 2023, on topics ranging from explainability to language modelling.
Explaining Interactions Between Text Spans. Sagnik Ray Choudhury, Pepa Atanasova, Isabelle Augenstein.
Why Should This Article Be Deleted? Transparent Stance Detection in Multilingual Wikipedia Editor Discussions. Lucie-Aimée Kaffee, Arnav Arora, Isabelle Augenstein.
Thorny Roses: Investigating the Dual Use Dilemma in Natural Language Processing. Lucie-Aimée Kaffee, Arnav Arora, Zeerak Talat, Isabelle Augenstein.
4 papers by CopeNLU authors are accepted to appear at ACL 2023. The papers make contributions within faithfulness of explanations, measuring intersectional biases, event extraction and few-shot stance detection.
Topic-Guided Sampling For Data-Efficient Multi-Domain Stance Detection. Erik Arakelyan, Arnav Arora, Isabelle Augenstein.
Faithfulness Tests for Natural Language Explanations. Pepa Atanasova, Oana-Maria Camburu, Christina Lioma, Thomas Lukasiewicz, Jakob Grue Simonsen, Isabelle Augenstein.
Measuring Intersectional Biases in Historical Documents. Nadav Borenstein, Karolina Stańczak, Thea Rolskov, Natacha Klein Käfer, Natália da Silva Perez, Isabelle Augenstein.
3 papers by CopeNLU authors are accepted to appear at NAACL 2022, which are on the topics of hatespeech detection, misinformation detection and multilingual probing.
Counterfactually Augmented Data and Unintended Bias: The Case of Sexism and Hate Speech Detection. Indira Sen, Mattia Samory, Claudia Wagner, Isabelle Augenstein.
A Survey on Stance Detection for Mis- and Disinformation Identification. Momchil Hardalov, Arnav Arora, Preslav Nakov, Isabelle Augenstein.
Same Neurons, Different Languages: Probing Morphosyntax in Multilingual Pre-trained Models.
A paper by CopeNLU author is accepted to appear at EACL 2021. The paper aims to bridge the gap between high- and low-resource languages by investigating to what degree cross-lingual models share structural information about languages.
Does Typological Blinding Impede Cross-Lingual Sharing?. Johannes Bjerva, Isabelle Augenstein.
2 papers by CopeNLU authors are accepted to appear at ACL 2020. One paper is on explainable fact checking, providing the first study of how fact checking explanations can be generated automatically based on claim content, and how this task can be modelled jointly with veracity prediction; whereas the other one is on script conversion, proposing a novel Chinese character conversion model that can disambiguate between mappings and convert between Chinese scripts.
Training models to work well for multiple languages, including low-resource ones