Publications

2024

Maximilian Maurer, Tanise Ceron, Sebastian Padó, Gabriella Lapesa. 2024. Toeing the Party Line: Election Manifestos as a Key to Understand Political Discourse on Twitter. In Findings of the Association for Computational Linguistics: EMNLP 2024, pages 6115–6130, Miami, Florida, USA.
Tanise Ceron, Neele Falk, Ana Baric, Dmitry Nikolaev, and Sebastian Padó. 2024. Beyond prompt brittleness: Evaluating the reliability and consistency of political worldviews in LLMs. TACL (Transactions of the Association for Computational Linguistics), volume 12.
Tanise Ceron, Ana Baric, André Blessing, Sebastian Haunss, Jonas Kuhn, Gabriella Lapesa, Sebastian Padó, Sean Papay and Patricia F. Zauchner. 2024. Automatic Analysis of Political Debates and Manifestos: Successes and Challenges. In Proceedings of the 1st International Conference on Recent Advances in Robust Argumentation Machines (RATIO-24). Springer Nature.

Tanise Ceron, Dmitry Nikolaev, and Sebastian Padó. 2023.Additive manifesto decomposition: A policy domain aware method for understanding party positioning. In Findings of the Association for Computational Linguistics: ACL 2023, pages 7874–7890, Toronto, Canada.
Dmitry Nikolaev, Tanise Ceron, and Sebastian Padó. 2023. Multilingual estimation of political-party positioning: From label aggregation to long-input Transformers. In Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, pages 9497–9511, Singapore.

Nico Blokker, Tanise Ceron, Andrea Blessing, Erenay Dayanik, Sebastian Haunss, Jonas Kuhn, Gabriella Lapesa and Sebastian Pado. 2022. Why justifications of claims matter for understanding party positions. In Proceedings of the 2nd workshop on computational linguistics for political text analysis.
Tanise Ceron, Nhut Truong, and Aurelie Herbelot. 2022. Algorithmic Diversity and Tiny Models: Comparing Binary Networks and the Fruit Fly Algorithm on Document Representation Tasks. In Proceedings of The Third Workshop on Simple and Efficient Natural Language Processing (SustaiNLP), pages 17–28, Abu Dhabi, United Arab Emirates (Hybrid).
Tanise Ceron, Nico Blokker, and Sebastian Padó. 2022. Optimizing text representations to capture (dis)similarity between political parties. In Proceedings of the 26th Conference on Computational Natural Language Learning (CoNLL), pages 325–338, Abu Dhabi, United Arab Emirates (Hybrid).

Tanise Ceron and Camilla Casula. (2021). Exploiting Contextualized Word Representations to Profile Haters on Twitter. In CLEF (Working Notes) (pp. 1871-1882).