Flavien Prost

According to our database, Flavien Prost authored at least 13 papers between 2019 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

InfAlign: Inference-aware language model alignment.

Ananth Balashankar, Ziteng Sun, Jonathan Berant, Jacob Eisenstein, Michael Collins, Adrian Hutter, Jong Lee, Chirag Nagpal, Flavien Prost, Aradhana Sinha, Ananda Theertha Suresh, Ahmad Beirami

CoRR, 2024

Inducing Group Fairness in LLM-Based Decisions.

James Atwood, Preethi Lahoti, Ananth Balashankar, Flavien Prost, Ahmad Beirami

CoRR, 2024

FRAPPÉ: A Group Fairness Framework for Post-Processing Everything.

Alexandru Tifrea, Preethi Lahoti, Ben Packer, Yoni Halpern, Ahmad Beirami, Flavien Prost

Proceedings of the Forty-first International Conference on Machine Learning, 2024

2023

FRAPPÉ: A Post-Processing Framework for Group Fairness Regularization.

Alexandru Tifrea, Preethi Lahoti, Ben Packer, Yoni Halpern, Ahmad Beirami, Flavien Prost

CoRR, 2023

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

2022

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

2021

Measuring Recommender System Effects with Simulated Users.

Sirui Yao, Yoni Halpern, Nithum Thain, Xuezhi Wang, Kang Lee, Flavien Prost, Ed H. Chi, Jilin Chen, Alex Beutel

CoRR, 2021

Practical Compositional Fairness: Understanding Fairness in Multi-Component Recommender Systems.

Xuezhi Wang, Nithum Thain, Anu Sinha, Flavien Prost, Ed H. Chi, Jilin Chen, Alex Beutel

Proceedings of the WSDM '21, 2021

Understanding and Improving Fairness-Accuracy Trade-offs in Multi-Task Learning.

Yuyan Wang, Xuezhi Wang, Alex Beutel, Flavien Prost, Jilin Chen, Ed H. Chi

Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021

Measuring Model Fairness under Noisy Covariates: A Theoretical Perspective.

Flavien Prost, Pranjal Awasthi, Nick Blumm, Aditee Kumthekar, Trevor Potter, Li Wei, Xuezhi Wang, Ed H. Chi, Jilin Chen, Alex Beutel

Proceedings of the AIES '21: AAAI/ACM Conference on AI, 2021

2020

Fairness without Demographics through Adversarially Reweighted Learning.

Preethi Lahoti, Alex Beutel, Jilin Chen, Kang Lee, Flavien Prost, Nithum Thain, Xuezhi Wang, Ed H. Chi

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

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

Debiasing Embeddings for Reduced Gender Bias in Text Classification.

Flavien Prost, Nithum Thain, Tolga Bolukbasi

CoRR, 2019