Questioning causality on sex, gender and COVID-19, and identifying bias in large-scale data-driven analyses: the Bias Priority Recommendations and Bias Catalog for Pandemics. - Natalia Díaz Rodríguez; Ruta Binkyte-Sadauskiene; Wafae Bakkali; Sannidhi Bookseller; Paola Tubaro; Andrius Bacevicius; Raja G. Chatila (CoRR, 2021)

Causal Discovery for Fairness. - Ruta Binkyte; Karima Makhlouf; Carlos Pinzón; Sami Zhioua; Catuscia Palamidessi (AFCP, 2022)

On the Need and Applicability of Causality for Fair Machine Learning. - Ruta Binkyte; Sami Zhioua (CoRR, 2022)

Shedding light on underrepresentation and Sampling Bias in machine learning. - Sami Zhioua; Ruta Binkyte (CoRR, 2023)

BaBE: Enhancing Fairness via Estimation of Latent Explaining Variables. - Ruta Binkyte; Daniele Gorla; Catuscia Palamidessi (CoRR, 2023)

Dissecting Causal Biases. - Ruta Binkyte; Sami Zhioua; Yassine Turki (CoRR, 2023)

Distant Reading and Viewing: "Big Questions" in Digital Art History and Digital Literary Studies. - Ruta Binkyte (Digit. Humanit. Q., 2023)

Advancing Ethical AI: Methods for fairness enhancement leveraging on causality and under privacy constraints. (Advancing Ethical AI: Methods for fairness enhancement leveraging on causality and under privacy constraints). - Ruta Binkyte (2023)

Gender and sex bias in COVID-19 epidemiological data through the lens of causality. - Natalia Díaz Rodríguez; Ruta Binkyte; Wafae Bakkali; Sannidhi Bookseller; Paola Tubaro; Andrius Bacevicius; Sami Zhioua; Raja Chatila 001 (Inf. Process. Manag., 2023)

Causal Discovery Under Local Privacy. - Ruta Binkyte; Carlos Pinzón; Szilvia Lestyan; Kangsoo Jung; Héber Hwang Arcolezi; Catuscia Palamidessi (CLeaR, 2024)

BaBE: Enhancing Fairness via Estimation of Explaining Variables. - Ruta Binkyte; Daniele Gorla; Catuscia Palamidessi (FAccT, 2024)

LLM4GRN: Discovering Causal Gene Regulatory Networks with LLMs - Evaluation through Synthetic Data Generation. - Tejumade Afonja; Ivaxi Sheth; Ruta Binkyte; Waqar Hanif; Thomas Ulas; Matthias Becker 003; Mario Fritz (CoRR, 2024)

Safety is Essential for Responsible Open-Ended Systems. - Ivaxi Sheth; Jan Wehner; Sahar Abdelnabi; Ruta Binkyte; Mario Fritz (CoRR, 2025)

Causality Is Key to Understand and Balance Multiple Goals in Trustworthy ML and Foundation Models. - Ruta Binkyte; Ivaxi Sheth; Zhijing Jin 001; Mohammad Havaei; Bernhard Schölkopf; Mario Fritz (CoRR, 2025)

On the Origins of Sampling Bias: Implications on Fairness Measurement and Mitigation. - Sami Zhioua; Ruta Binkyte; Ayoub Ouni; Farah Barika Ktata (CoRR, 2025)

Interactional Fairness in LLM Multi-Agent Systems: An Evaluation Framework. - Ruta Binkyte (CoRR, 2025)

Justice in Judgment: Unveiling (Hidden) Bias in LLM-assisted Peer Reviews. - Sai Suresh Macharla Vasu; Ivaxi Sheth; Hui-Po Wang; Ruta Binkyte; Mario Fritz (CoRR, 2025)