Debiasing Embeddings for Reduced Gender Bias in Text Classification. - Flavien Prost; Nithum Thain; Tolga Bolukbasi (CoRR, 2019)

Toward a better trade-off between performance and fairness with kernel-based distribution matching. - Flavien Prost; Hai Qian; Qiuwen Chen; Ed H. Chi; Jilin Chen; Alex Beutel (CoRR, 2019)

Fairness without Demographics through Adversarially Reweighted Learning. - Preethi Lahoti; Alex Beutel; Jilin Chen; Kang Lee; Flavien Prost; Nithum Thain; Xuezhi Wang 002; Ed H. Chi (NeurIPS, 2020)

Measuring Model Fairness under Noisy Covariates: A Theoretical Perspective. - Flavien Prost; Pranjal Awasthi; Nick Blumm; Aditee Kumthekar; Trevor Potter; Li Wei; Xuezhi Wang 002; Ed H. Chi; Jilin Chen; Alex Beutel (AIES, 2021)

Understanding and Improving Fairness-Accuracy Trade-offs in Multi-Task Learning. - Yuyan Wang; Xuezhi Wang 002; Alex Beutel; Flavien Prost; Jilin Chen; Ed H. Chi (KDD, 2021)

Practical Compositional Fairness: Understanding Fairness in Multi-Component Recommender Systems. - Xuezhi Wang 002; Nithum Thain; Anu Sinha; Flavien Prost; Ed H. Chi; Jilin Chen; Alex Beutel (WSDM, 2021)

Measuring Recommender System Effects with Simulated Users. - Sirui Yao; Yoni Halpern; Nithum Thain; Xuezhi Wang 002; Kang Lee; Flavien Prost; Ed H. Chi; Jilin Chen; Alex Beutel (CoRR, 2021)

Simpson's Paradox in Recommender Fairness: Reconciling differences between per-user and aggregated evaluations. - Flavien Prost; Ben Packer; Jilin Chen; Li Wei; Pierre Kremp; Nick Blumm; Susan Wang; Tulsee Doshi; Tonia Osadebe; Lukasz Heldt; Ed H. Chi; Alex Beutel (CoRR, 2022)

Towards A Scalable Solution for Improving Multi-Group Fairness in Compositional Classification. - James Atwood; Tina Tian; Ben Packer; Meghana Deodhar; Jilin Chen; Alex Beutel; Flavien Prost; Ahmad Beirami (CoRR, 2023)

FRAPPÉ: A Post-Processing Framework for Group Fairness Regularization. - Alexandru Tifrea; Preethi Lahoti; Ben Packer; Yoni Halpern; Ahmad Beirami; Flavien Prost (CoRR, 2023)

FRAPPÉ: A Group Fairness Framework for Post-Processing Everything. - Alexandru Tifrea; Preethi Lahoti; Ben Packer; Yoni Halpern; Ahmad Beirami; Flavien Prost (ICML, 2024)

Inducing Group Fairness in LLM-Based Decisions. - James Atwood; Preethi Lahoti; Ananth Balashankar; Flavien Prost; Ahmad Beirami (CoRR, 2024)

InfAlign: Inference-aware language model alignment. - Ananth Balashankar; Ziteng Sun; Jonathan Berant; Jacob Eisenstein; Michael Collins 001; Adrian Hutter; Jong Lee; Chirag Nagpal; Flavien Prost; Aradhana Sinha; Ananda Theertha Suresh; Ahmad Beirami (CoRR, 2024)