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Alex Beutel
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Publications
- 2024
- [j8]Aradhana Sinha, Ananth Balashankar, Ahmad Beirami, Thi Avrahami, Jilin Chen, Alex Beutel:
Break it, Imitate it, Fix it: Robustness by Generating Human-Like Attacks. Trans. Mach. Learn. Res. 2024 (2024) - [c58]Hansa Srinivasan
, Candice Schumann
Generalized People Diversity: Learning a Human Perception-Aligned Diversity Representation for People Images. FAccT 2024: 797-821 - [c57]Sidharth Mudgal, Jong Lee, Harish Ganapathy, YaGuang Li, Tao Wang, Yanping Huang, Zhifeng Chen, Heng-Tze Cheng, Michael Collins, Trevor Strohman, Jilin Chen, Alex Beutel, Ahmad Beirami:
Controlled Decoding from Language Models. ICML 2024 - [i52]Hansa Srinivasan, Candice Schumann, Aradhana Sinha, David Madras, Gbolahan Oluwafemi Olanubi, Alex Beutel, Susanna Ricco, Jilin Chen:
Generalized People Diversity: Learning a Human Perception-Aligned Diversity Representation for People Images. CoRR abs/2401.14322 (2024) - 2023
- [c55]Ananth Balashankar, Xuezhi Wang, Yao Qin, Ben Packer, Nithum Thain, Ed H. Chi, Jilin Chen, Alex Beutel:
Improving Classifier Robustness through Active Generative Counterfactual Data Augmentation. EMNLP (Findings) 2023: 127-139 - [c54]Preethi Lahoti, Nicholas Blumm, Xiao Ma, Raghavendra Kotikalapudi, Sahitya Potluri, Qijun Tan, Hansa Srinivasan, Ben Packer, Ahmad Beirami, Alex Beutel, Jilin Chen:
Improving Diversity of Demographic Representation in Large Language Models via Collective-Critiques and Self-Voting. EMNLP 2023: 10383-10405 - [i41]Ananth Balashankar, Xuezhi Wang, Yao Qin, Ben Packer, Nithum Thain, Jilin Chen, Ed H. Chi, Alex Beutel:
Improving Classifier Robustness through Active Generation of Pairwise Counterfactuals. CoRR abs/2305.13535 (2023) - [i40]Xiao Ma, Swaroop Mishra, Ahmad Beirami, Alex Beutel, Jilin Chen:
Let's Do a Thought Experiment: Using Counterfactuals to Improve Moral Reasoning. CoRR abs/2306.14308 (2023) - [i39]James Atwood, Tina Tian, Ben Packer, Meghana Deodhar, Jilin Chen, Alex Beutel, Flavien Prost, Ahmad Beirami:
Towards A Scalable Solution for Improving Multi-Group Fairness in Compositional Classification. CoRR abs/2307.05728 (2023) - [i37]Preethi Lahoti, Nicholas Blumm, Xiao Ma, Raghavendra Kotikalapudi, Sahitya Potluri, Qijun Tan, Hansa Srinivasan, Ben Packer, Ahmad Beirami, Alex Beutel, Jilin Chen:
Improving Diversity of Demographic Representation in Large Language Models via Collective-Critiques and Self-Voting. CoRR abs/2310.16523 (2023) - [i36]Aradhana Sinha, Ananth Balashankar, Ahmad Beirami, Thi Avrahami, Jilin Chen, Alex Beutel:
Break it, Imitate it, Fix it: Robustness by Generating Human-Like Attacks. CoRR abs/2310.16955 (2023) - [i35]Ananth Balashankar, Xiao Ma, Aradhana Sinha, Ahmad Beirami, Yao Qin, Jilin Chen, Alex Beutel:
Improving Few-shot Generalization of Safety Classifiers via Data Augmented Parameter-Efficient Fine-Tuning. CoRR abs/2310.16959 (2023) - [i34]Sidharth Mudgal, Jong Lee, Harish Ganapathy, YaGuang Li, Tao Wang, Yanping Huang, Zhifeng Chen, Heng-Tze Cheng, Michael Collins, Trevor Strohman, Jilin Chen, Alex Beutel, Ahmad Beirami:
Controlled Decoding from Language Models. CoRR abs/2310.17022 (2023) - 2022
- [c50]Meghana Deodhar, Xiao Ma, Yixin Cai, Alex Koes, Alex Beutel, Jilin Chen:
A human-ML collaboration framework for improving video content reviews. CIKM Workshops 2022 - [i32]Zee Fryer, Vera Axelrod, Ben Packer, Alex Beutel, Jilin Chen, Kellie Webster:
Flexible text generation for counterfactual fairness probing. CoRR abs/2206.13757 (2022) - [i31]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:
Simpson's Paradox in Recommender Fairness: Reconciling differences between per-user and aggregated evaluations. CoRR abs/2210.07755 (2022) - [i30]Meghana Deodhar, Xiao Ma, Yixin Cai, Alex Koes, Alex Beutel, Jilin Chen:
A Human-ML Collaboration Framework for Improving Video Content Reviews. CoRR abs/2210.09500 (2022) - 2021
- [c48]Flavien Prost, Pranjal Awasthi, Nick Blumm, Aditee Kumthekar, Trevor Potter, Li Wei, Xuezhi Wang, Ed H. Chi, Jilin Chen, Alex Beutel:
Measuring Model Fairness under Noisy Covariates: A Theoretical Perspective. AIES 2021: 873-883 - [c45]Yuyan Wang, Xuezhi Wang, Alex Beutel, Flavien Prost, Jilin Chen, Ed H. Chi:
Understanding and Improving Fairness-Accuracy Trade-offs in Multi-Task Learning. KDD 2021: 1748-1757 - [c43]Xuezhi Wang, Nithum Thain, Anu Sinha, Flavien Prost, Ed H. Chi, Jilin Chen, Alex Beutel:
Practical Compositional Fairness: Understanding Fairness in Multi-Component Recommender Systems. WSDM 2021: 436-444 - [i28]Sirui Yao, Yoni Halpern, Nithum Thain, Xuezhi Wang, Kang Lee, Flavien Prost, Ed H. Chi, Jilin Chen, Alex Beutel:
Measuring Recommender System Effects with Simulated Users. CoRR abs/2101.04526 (2021) - [i25]Flavien Prost, Pranjal Awasthi, Nick Blumm, Aditee Kumthekar, Trevor Potter, Li Wei, Xuezhi Wang, Ed H. Chi, Jilin Chen, Alex Beutel:
Measuring Model Fairness under Noisy Covariates: A Theoretical Perspective. CoRR abs/2105.09985 (2021) - [i24]Yuyan Wang, Xuezhi Wang, Alex Beutel, Flavien Prost, Jilin Chen, Ed H. Chi:
Understanding and Improving Fairness-Accuracy Trade-offs in Multi-Task Learning. CoRR abs/2106.02705 (2021) - 2020
- [c40]Tianlu Wang, Xuezhi Wang, Yao Qin, Ben Packer, Kang Li, Jilin Chen, Alex Beutel, Ed H. Chi:
CAT-Gen: Improving Robustness in NLP Models via Controlled Adversarial Text Generation. EMNLP (1) 2020: 5141-5146 - [c39]Preethi Lahoti, Alex Beutel, Jilin Chen, Kang Lee, Flavien Prost, Nithum Thain, Xuezhi Wang, Ed H. Chi:
Fairness without Demographics through Adversarially Reweighted Learning. NeurIPS 2020 - [i22]Preethi Lahoti, Alex Beutel, Jilin Chen, Kang Lee, Flavien Prost, Nithum Thain, Xuezhi Wang, Ed H. Chi:
Fairness without Demographics through Adversarially Reweighted Learning. CoRR abs/2006.13114 (2020) - [i20]Tianlu Wang, Xuezhi Wang, Yao Qin, Ben Packer, Kang Li, Jilin Chen, Alex Beutel, Ed H. Chi:
CAT-Gen: Improving Robustness in NLP Models via Controlled Adversarial Text Generation. CoRR abs/2010.02338 (2020) - [i19]Kellie Webster, Xuezhi Wang, Ian Tenney, Alex Beutel, Emily Pitler, Ellie Pavlick, Jilin Chen, Slav Petrov:
Measuring and Reducing Gendered Correlations in Pre-trained Models. CoRR abs/2010.06032 (2020) - 2019
- [c36]Alex Beutel, Jilin Chen, Tulsee Doshi, Hai Qian, Allison Woodruff, Christine Luu, Pierre Kreitmann, Jonathan Bischof, Ed H. Chi:
Putting Fairness Principles into Practice: Challenges, Metrics, and Improvements. AIES 2019: 453-459 - [c34]Alex Beutel, Jilin Chen, Tulsee Doshi, Hai Qian, Li Wei, Yi Wu, Lukasz Heldt, Zhe Zhao, Lichan Hong, Ed H. Chi, Cristos Goodrow:
Fairness in Recommendation Ranking through Pairwise Comparisons. KDD 2019: 2212-2220 - [i16]Alex Beutel, Jilin Chen, Tulsee Doshi, Hai Qian, Allison Woodruff, Christine Luu, Pierre Kreitmann, Jonathan Bischof, Ed H. Chi:
Putting Fairness Principles into Practice: Challenges, Metrics, and Improvements. CoRR abs/1901.04562 (2019) - [i14]Alex Beutel, Jilin Chen, Tulsee Doshi, Hai Qian, Li Wei, Yi Wu, Lukasz Heldt, Zhe Zhao, Lichan Hong, Ed H. Chi, Cristos Goodrow:
Fairness in Recommendation Ranking through Pairwise Comparisons. CoRR abs/1903.00780 (2019) - [i13]Candice Schumann, Xuezhi Wang, Alex Beutel, Jilin Chen, Hai Qian, Ed H. Chi:
Transfer of Machine Learning Fairness across Domains. CoRR abs/1906.09688 (2019) - [i12]Flavien Prost, Hai Qian, Qiuwen Chen, Ed H. Chi, Jilin Chen, Alex Beutel:
Toward a better trade-off between performance and fairness with kernel-based distribution matching. CoRR abs/1910.11779 (2019) - [i11]Xuezhi Wang, Nithum Thain, Anu Sinha, Ed H. Chi, Jilin Chen, Alex Beutel:
Practical Compositional Fairness: Understanding Fairness in Multi-Task ML Systems. CoRR abs/1911.01916 (2019) - 2018
- [c29]Qian Zhao, Jilin Chen, Minmin Chen, Sagar Jain, Alex Beutel, Francois Belletti, Ed H. Chi:
Categorical-attributes-based item classification for recommender systems. RecSys 2018: 320-328 - 2017
- [i7]Alex Beutel, Jilin Chen, Zhe Zhao, Ed H. Chi:
Data Decisions and Theoretical Implications when Adversarially Learning Fair Representations. CoRR abs/1707.00075 (2017)
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