Flavien Prost - RankMe

17 papers A* 4A 1C 1Journal 11

Year	Rank	Type	Title / Venue / Authors
2025	A*	`conf`	InfAlign: Inference-aware language model alignment. ICML 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
2024	A*	`conf`	FRAPPÉ: A Group Fairness Framework for Post-Processing Everything. ICML Alexandru Tifrea, Preethi Lahoti, Ben Packer, Yoni Halpern, Ahmad Beirami, Flavien Prost
2024	J	`jnl`	Inducing Group Fairness in LLM-Based Decisions. CoRR James Atwood, Preethi Lahoti, Ananth Balashankar, Flavien Prost, Ahmad Beirami
2024	J	`jnl`	InfAlign: Inference-aware language model alignment. CoRR 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
2023	J	`jnl`	FRAPPÉ: A Post-Processing Framework for Group Fairness Regularization. CoRR Alexandru Tifrea, Preethi Lahoti, Ben Packer, Yoni Halpern, Ahmad Beirami, Flavien Prost
2023	J	`jnl`	Towards A Scalable Solution for Improving Multi-Group Fairness in Compositional Classification. CoRR James Atwood, Tina Tian, Ben Packer, Meghana Deodhar, Jilin Chen, Alex Beutel, Flavien Prost, Ahmad Beirami
2022	J	`jnl`	Simpson's Paradox in Recommender Fairness: Reconciling differences between per-user and aggregated evaluations. CoRR 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
2021	C	`conf`	Measuring Model Fairness under Noisy Covariates: A Theoretical Perspective. AIES Flavien Prost, Pranjal Awasthi, Nick Blumm, Aditee Kumthekar, Trevor Potter, Li Wei, Xuezhi Wang, Ed H. Chi, Jilin Chen, Alex Beutel
2021	J	`jnl`	Measuring Model Fairness under Noisy Covariates: A Theoretical Perspective. CoRR Flavien Prost, Pranjal Awasthi, Nick Blumm, Aditee Kumthekar, Trevor Potter, Li Wei, Xuezhi Wang, Ed H. Chi, Jilin Chen, Alex Beutel
2021	J	`jnl`	Measuring Recommender System Effects with Simulated Users. CoRR Sirui Yao, Yoni Halpern, Nithum Thain, Xuezhi Wang, Kang Lee, Flavien Prost, Ed H. Chi, Jilin Chen, Alex Beutel
2021	A	`conf`	Practical Compositional Fairness: Understanding Fairness in Multi-Component Recommender Systems. WSDM Xuezhi Wang, Nithum Thain, Anu Sinha, Flavien Prost, Ed H. Chi, Jilin Chen, Alex Beutel
2021	A*	`conf`	Understanding and Improving Fairness-Accuracy Trade-offs in Multi-Task Learning. KDD Yuyan Wang, Xuezhi Wang, Alex Beutel, Flavien Prost, Jilin Chen, Ed H. Chi
2021	J	`jnl`	Understanding and Improving Fairness-Accuracy Trade-offs in Multi-Task Learning. CoRR Yuyan Wang, Xuezhi Wang, Alex Beutel, Flavien Prost, Jilin Chen, Ed H. Chi
2020	A*	`conf`	Fairness without Demographics through Adversarially Reweighted Learning. NeurIPS Preethi Lahoti, Alex Beutel, Jilin Chen, Kang Lee, Flavien Prost, Nithum Thain, Xuezhi Wang, Ed H. Chi
2020	J	`jnl`	Fairness without Demographics through Adversarially Reweighted Learning. CoRR Preethi Lahoti, Alex Beutel, Jilin Chen, Kang Lee, Flavien Prost, Nithum Thain, Xuezhi Wang, Ed H. Chi
2019	J	`jnl`	Debiasing Embeddings for Reduced Gender Bias in Text Classification. CoRR Flavien Prost, Nithum Thain, Tolga Bolukbasi
2019	J	`jnl`	Toward a better trade-off between performance and fairness with kernel-based distribution matching. CoRR Flavien Prost, Hai Qian, Qiuwen Chen, Ed H. Chi, Jilin Chen, Alex Beutel