Debora Nozza
I am Assistant Professor working on natural language processing at Bocconi University. I have been awarded a €1.5m ERC Starting Grant project 2023 for research on personalized and subjective approaches to Natural Language Processing. My work focuses on ethics and Natural Language Processing, more specifically on abusive language detection.
About
I have been awarded a €1.5m ERC Starting Grant project 2023 for research on personalized and subjective approaches to Natural Language Processing.
Research interests
My research interests mainly focus on Natural Language Processing, specifically on the detection and counter-acting of hate speech and algorithmic bias on Social Media data in multilingual context.
Selected Publications
Exposing the limits of zero-shot cross-lingual hate speech detection
Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics, 2021Entropy-based attention regularization frees unintended bias mitigation from lists
Findings of the Association for Computational Linguistics: ACL 2022, 2022HONEST: measuring hurtful sentence completion in language models
Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2021Unintended bias in misogyny detection
2019 IEEE/WIC/ACM International Conference on Web Intelligence (WI 2019) proceedings : Thessaloniki, Greece, 13-17 October 2019, 2019A tale of pronouns: interpretability informs gender bias mitigation for fairer instruction-tuned machine translation
Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023What about em? How commercial Machine Translation fails to handle (neo-)pronouns
Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2023Easily accessible Text-to-Image generation amplifies demographic stereotypes at large scale
FAccT '23: Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency, 2023Metrics for what, metrics for whom: assessing actionability of bias evaluation metrics in NLP
Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, 2024Teaching
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MACHINE LEARNING AND ARTIFICIAL INTELLIGENCE LAB
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