Lily H. Zhang

23 papers A* 8Journal 13Unranked 2
YearRankTypeTitle / Venue / Authors
2025 A* conf
Learning from others' mistakes: Finetuning machine translation models with span-level error annotations.
ICML
Lily H. Zhang, Hamid Dadkhahi, Mara Finkelstein, Firas Trabelsi, Jiaming Luo, Markus Freitag
2025 A* conf
Preference learning made easy: Everything should be understood through win rate.
ICML
Lily H. Zhang, Rajesh Ranganath
2025 J jnl
Preference learning made easy: Everything should be understood through win rate.
CoRR
Lily H. Zhang, Rajesh Ranganath
2024 J jnl
Learning from others' mistakes: Finetuning machine translation models with span-level error annotations.
CoRR
Lily H. Zhang, Hamid Dadkhahi, Mara Finkelstein, Firas Trabelsi, Jiaming Luo, Markus Freitag
2024 A* conf
Preference Learning Algorithms Do Not Learn Preference Rankings.
NeurIPS
Angelica Chen, Sadhika Malladi, Lily H. Zhang, Xinyi Chen, Qiuyi (Richard) Zhang, Rajesh Ranganath, Kyunghyun Cho
2024 J jnl
Preference Learning Algorithms Do Not Learn Preference Rankings.
CoRR
Angelica Chen, Sadhika Malladi, Lily H. Zhang, Xinyi Chen, Qiuyi Zhang, Rajesh Ranganath, Kyunghyun Cho
2024 J jnl
Robust Anomaly Detection for Particle Physics Using Multi-Background Representation Learning.
CoRR
Abhijith Gandrakota, Lily H. Zhang, Aahlad Manas Puli, Kyle Cranmer, Jennifer Ngadiuba, Rajesh Ranganath, Nhan Tran
2024 J jnl
Robust anomaly detection for particle physics using multi-background representation learning.
Mach. Learn. Sci. Technol.
Abhijith Gandrakota, Lily H. Zhang, Aahlad Manas Puli, Kyle Cranmer, Jennifer Ngadiuba, Rajesh Ranganath, Nhan Tran
2024 J jnl
Towards Minimal Targeted Updates of Language Models with Targeted Negative Training.
CoRR
Lily H. Zhang, Rajesh Ranganath, Arya Tafvizi
2024 J jnl
Towards Minimal Targeted Updates of Language Models with Targeted Negative Training.
Trans. Mach. Learn. Res.
Lily H. Zhang, Rajesh Ranganath, Arya Tafvizi
2023 A* conf
Don't blame Dataset Shift! Shortcut Learning due to Gradients and Cross Entropy.
NeurIPS
Aahlad Manas Puli, Lily H. Zhang, Yoav Wald, Rajesh Ranganath
2023 J jnl
Don't blame Dataset Shift! Shortcut Learning due to Gradients and Cross Entropy.
CoRR
Aahlad Manas Puli, Lily H. Zhang, Yoav Wald, Rajesh Ranganath
2023 A* conf
Robustness to Spurious Correlations Improves Semantic Out-of-Distribution Detection.
AAAI
Lily H. Zhang, Rajesh Ranganath
2023 J jnl
Robustness to Spurious Correlations Improves Semantic Out-of-Distribution Detection.
CoRR
Lily H. Zhang, Rajesh Ranganath
2023 — conf
When More is Less: Incorporating Additional Datasets Can Hurt Performance By Introducing Spurious Correlations.
MLHC
Rhys Compton, Lily H. Zhang, Aahlad Manas Puli, Rajesh Ranganath
2023 J jnl
When More is Less: Incorporating Additional Datasets Can Hurt Performance By Introducing Spurious Correlations.
CoRR
Rhys Compton, Lily H. Zhang, Aahlad Manas Puli, Rajesh Ranganath
2022 A* conf
Out-of-distribution Generalization in the Presence of Nuisance-Induced Spurious Correlations.
ICLR
Aahlad Manas Puli, Lily H. Zhang, Eric Karl Oermann, Rajesh Ranganath
2022 A* conf
Set Norm and Equivariant Skip Connections: Putting the Deep in Deep Sets.
ICML
Lily H. Zhang, Veronica Tozzo, John M. Higgins, Rajesh Ranganath
2022 J jnl
Set Norm and Equivariant Skip Connections: Putting the Deep in Deep Sets.
CoRR
Lily H. Zhang, Veronica Tozzo, John M. Higgins, Rajesh Ranganath
2021 J jnl
Predictive Modeling in the Presence of Nuisance-Induced Spurious Correlations.
CoRR
Aahlad Manas Puli, Lily H. Zhang, Eric K. Oermann, Rajesh Ranganath
2021 A* conf
Understanding Failures in Out-of-Distribution Detection with Deep Generative Models.
ICML
Lily H. Zhang, Mark Goldstein, Rajesh Ranganath
2021 J jnl
Understanding Failures in Out-of-Distribution Detection with Deep Generative Models.
CoRR
Lily H. Zhang, Mark Goldstein, Rajesh Ranganath
2019 — conf
Rapid Model Comparison by Amortizing Across Models.
AABI
Lily H. Zhang, Michael C. Hughes