Differentially Private Natural Language Models: Recent Advances and Future Directions
L. Hu, I. Habernal, L. Shen, D. Wang, in: Y. Graham, M. Purver (Eds.), Findings of the Association for Computational Linguistics: EACL 2024, St. Julian’s, Malta, March 17-22, 2024, Association for Computational Linguistics, 2024, pp. 478–499.

DP-NMT: Scalable Differentially Private Machine Translation
T. Igamberdiev, D.N.L. Vu, F. Kuennecke, Z. Yu, J. Holmer, I. Habernal, in: N. Aletras, O. De Clercq (Eds.), Proceedings of the 18th Conference of the European Chapter of the Association for Computational Linguistics: System Demonstrations, Association for Computational Linguistics, St. Julians, Malta, 2024, pp. 94–105.

Privacy-Preserving Natural Language Processing
I. Habernal, F. Mireshghallah, P. Thaine, S. Ghanavati, O. Feyisetan, in: Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics: Tutorial Abstracts, Association for Computational Linguistics, 2023.

Trade-Offs Between Fairness and Privacy in Language Modeling
C. Matzken, S. Eger, I. Habernal, in: Findings of the Association for Computational Linguistics: ACL 2023, Association for Computational Linguistics, 2023.

Crowdsourcing on Sensitive Data with Privacy-Preserving Text Rewriting
N. Mouhammad, J. Daxenberger, B. Schiller, I. Habernal, in: Proceedings of the 17th Linguistic Annotation Workshop (LAW-XVII), Association for Computational Linguistics, 2023.

Privacy-Preserving Models for Legal Natural Language Processing
Y. Yin, I. Habernal, in: Proceedings of the Natural Legal Language Processing Workshop 2022, Association for Computational Linguistics, 2023.

How Much User Context Do We Need? Privacy by Design in Mental Health NLP Applications
R. Sawhney, A. Neerkaje, I. Habernal, L. Flek, Proceedings of the International AAAI Conference on Web and Social Media 17 (2023) 766–776.

One size does not fit all: Investigating strategies for differentially-private learning across NLP tasks
M. Senge, T. Igamberdiev, I. Habernal, in: Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, Association for Computational Linguistics, 2023.

DP-BART for Privatized Text Rewriting under Local Differential Privacy
T. Igamberdiev, I. Habernal, in: Findings of the Association for Computational Linguistics: ACL 2023, Association for Computational Linguistics, 2023.

The Legal Argument Reasoning Task in Civil Procedure
L. Bongard, L. Held, I. Habernal, in: Proceedings of the Natural Legal Language Processing Workshop 2022, Association for Computational Linguistics, 2023.

Mining legal arguments in court decisions
I. Habernal, D. Faber, N. Recchia, S. Bretthauer, I. Gurevych, I. Spiecker genannt Döhmann, C. Burchard, Artificial Intelligence and Law (2023).

DP-NMT: Scalable Differentially-Private Machine Translation
T. Igamberdiev, D.N.L. Vu, F. Künnecke, Z. Yu, J. Holmer, I. Habernal, (2023).

LaCour!: Enabling Research on Argumentation in Hearings of the European Court of Human Rights
L. Held, I. Habernal, (2023).

Privacy-Preserving Graph Convolutional Networks for Text Classification
T. Igamberdiev, I. Habernal, in: Proceedings of the Thirteenth Language Resources and Evaluation Conference, European Language Resources Association, Marseille, France, 2022, pp. 338–350.

DP-Rewrite: Towards Reproducibility and Transparency in Differentially Private Text Rewriting
T. Igamberdiev, T. Arnold, I. Habernal, in: Proceedings of the 29th International Conference on Computational Linguistics, International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 2022, pp. 2927–2933.

How reparametrization trick broke differentially-private text representation learning
I. Habernal, in: Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers), Association for Computational Linguistics, 2022.

When differential privacy meets NLP: The devil is in the detail
I. Habernal, in: Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, Association for Computational Linguistics, 2021.

Why do you think that? Exploring Faithful Sentence-Level Rationales Without Supervision
M. Glockner, I. Habernal, I. Gurevych, in: Findings of the Association for Computational Linguistics: EMNLP 2020, Association for Computational Linguistics, 2020.

The Argument Reasoning Comprehension Task: Identification and            Reconstruction of Implicit Warrants
I. Habernal, H. Wachsmuth, I. Gurevych, B. Stein, in: Proceedings of the 2018 Conference of the North American Chapter of          the Association for Computational Linguistics: Human Language          Technologies, Volume 1 (Long Papers), Association for Computational Linguistics, 2018.

Before Name-Calling: Dynamics and Triggers of Ad Hominem Fallacies            in Web Argumentation
I. Habernal, H. Wachsmuth, I. Gurevych, B. Stein, in: Proceedings of the 2018 Conference of the North American Chapter of          the Association for Computational Linguistics: Human Language          Technologies, Volume 1 (Long Papers), Association for Computational Linguistics, 2018.