• Aguilera, A., Montes, N., Curto, G., Osman, N., Sierra, C. (2024). Can poverty be reduced by acting on discrimination? An agent-based model for policy making.  22nd International Conference on Autonomous Agents and Multiagent Systems (AAMAS). 

• Curto, G., Kiritchenko, S., Nejadgholi, I., and Fraser, K. C., (2024). The Crime of Being Poor: Associations between Crime and Poverty on Social Media in Eight Countries. NAACL - North American Association for Computational Linguistics. 6th Workshop on Natural Language Processing and Computational Social Science (NLP+CSS). 

• Curto, G., Comim, F., (2023). SAF: Stakeholders' Agreement on Fairness in the Practice of Machine Learning Development. Science and Engineering Ethics. 

• Kiritchenko, S., Curto, G., Nejadgholi, I., Fraser, K. C., (2023). Aporophobia: An Overlooked Type of Toxic Language targeting the poor. ACL 2023 - Association of Computational Linguistics. 7th Workshop on Online Abuse and Harms (WOAH). Awarded Outstanding Paper .

• Curto, G., & Arnaiz, A., Oliver, N. (2023). Algorithms for Social Justice: Affirmative Action in Social Networks. Accessible through ArXiv. 

• Montes, N., Curto, G., Osman, N., Sierra, C. (2023). An Agent-Based Model for Poverty and Discrimination Policy- Making. Proceedings of the AMPM 2022: 2nd Workshop in Agent-based Modeling & Policy-Making, JURIX. 

• Curto, G., Montes, N. Comim, F., Osman, N., Sierra, C. (2022). A norm Optimization Approach to SDGs: Tackling Poverty by Acting on Discrimination. Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence (IJCAI'22). Track AI for Good (Best Project Award).

• Curto, G., Jojoa Acosta, M ., Comim, F., & Garcia-Zapirain, B. (2022). Are AI systems Biased Against the Poor? A Machine Learning Analysis Using Word2vec and GloVe Embeddings. AI and Society.

• Curto, G. (2002). Artificial Intelligence and Inclusion: An Analysis of Bias Against the Poor. Universitat Ramon Llull.

Under review: 

• Arnaiz, A., Curto, G., Oliver, N., (2024). Structural Group Unfairness: Measurement and Mitigation by means of the Effective Resistance. ACM Conference on Fairness, Accountability, and Transparency (ACM FAccT) 

Working papers: 

•  Curto, G., Kiritchenko, S., Nejadgholi, I., Fraser, K.C., (2024). The Crime of Being Poor: A Cross-Country Comparative Measurement Of Aporophobia In Twitter Through NLP. Target journal: 2024 Annual Conference of te North American Chapter of the Association for Computational Linguistics (NAACL-2024) (Accessible Through ArXiv).

• “110 Years of Poverty Bias Tracked by Large Language Models”. With Yang, Y., Lale, J. & Abbasi, A. Target journal: Proceedings of the National Academy of Sciences of the United States (PNAS).

• “Framing Analysis of Extreme Weather Events in the US News Media”. With Meareg Hailemariam. Target journal: Journal of Artificial Intelligence for Sustainable Development (JAISD).

• “Machine Learning-Based Indexes for the United Nations: accounting for public opinion in social networks and pre-labeling with ChatGPT”. With Kiritchenko, S., Nejadgholi, I., Fraser, K.C., Target journal: Proceedings of the AAAI Conference on Artificial Intelligence (track AI for social impact).

• “The View of Immigration in Academic Papers: An Analysis Using Machine Learning”. With Jojoa Acosta, M., Chaves, A., & Garcia-Zapirain, B. Target journal: AI & Society.

• Review of the Book: Cortina, A. (2022), Aporophobia : Why we Reject the Poor Instead of Helping Them. Princeton University Press. For the International Review of Social History (IRSH) journal, Springer.