Accepted Papers
- Causal Fair Machine Learning via Rank-Preserving Interventional Distributions -
Ludwig Bothmann, Susanne Dandl, Michael Schomaker
- Visualizing Bias in Activations of Deep Neural Networks as Topographic Maps -
Valerie Krug, Christopher Olson, Sebastian Stober
- Recommendations for Bias Mitigation Methods: Applicability and Legality -
Madeleine Waller, Odinaldo Rodrigues, Oana Cocarascu
- Reasoning With Bias -
Chiara Manganini, Giuseppe Primiero
- FAiRDAS: Fairness-Aware Ranking as Dynamic Abstract System -
Eleonora Misino, Roberta Calegari, Michele Lombardi, Michela Milano
- EXTRACT: Explainable Transparent Control of Bias in Embeddings -
Zhijin Guo, Zhaozhen Xu, Martha Lewis, Nello Cristianini
- Fairness in job recommendations: estimating, explaining, and reducing gender gaps -
Guillaume Bied, Christophe Gaillac, Morgane Hoffmann, Philippe Caillou, Bruno Crépon, Solal Nathan, Michèle Sebag
- Gender Bias in Multimodal Models: A Transnational Feminist Approach Considering Geographical Region and Culture -
Abhishek Mandal, Suzanne Little, Susan Leavy
- A geometric framework for fairness -
Alessandro Maggio, Luca Giuliani, Roberta Calegari, Michele Lombardi, Michela Milano
- Symbolic AI (LFIT) for XAI to handle biases -
Javier Tello, Marina de la Cruz, Tony Ribeiro, Julian Fierrez, Aythami Morales, Ruben Tolosana, César Luis Alonso, Alfonso Ortega
- Bias Mitigation for Large Language Models using Adversarial Learning -
Jasmina S. Ernst, Sascha Marton, Jannik Brinkmann, Eduardo Vellasques, Damien Foucard, Martin Kraemer, Marian Lambert
- Impact based fairness framework for socio-technical decision making -
Mattias Brännström, Lili Jiang, Andrea Aler Tubella, Virginia Dignum