Elliot Creager

41 papers A* 11Journal 24Unranked 5

Year	Rank	Type	Title / Venue / Authors
2026	—	`conf`	Say It Another Way: Auditing LLMs with a User-Grounded Automated Paraphrasing Framework. EACL (Volume 1: Long Papers) Cléa Chataigner, Rebecca Ma, Prakhar Ganesh, Yuhao Chen, Afaf Taïk, Elliot Creager, Golnoosh Farnadi
2025	J	`jnl`	Active Slice Discovery in Large Language Models. CoRR Minhui Zhang, Prahar Ijner, Yoav Wald, Elliot Creager
2025	J	`jnl`	Conscious Data Contribution via Community-Driven Chain-of-Thought Distillation. CoRR Lena Libon, Meghana Bhange, Rushabh Solanki, Elliot Creager, Ulrich Aïvodji
2025	J	`jnl`	Crowding Out The Noise: Algorithmic Collective Action Under Differential Privacy. CoRR Rushabh Solanki, Meghana Bhange, Ulrich Aïvodji, Elliot Creager
2025	J	`jnl`	Say It Another Way: Auditing LLMs with a User-Grounded Automated Paraphrasing Framework. CoRR Cléa Chataigner, Rebecca Ma, Prakhar Ganesh, Afaf Taïk, Elliot Creager, Golnoosh Farnadi
2025	J	`jnl`	Transformers Don't In-Context Learn Least Squares Regression. CoRR Joshua Hill, Benjamin Eyre, Elliot Creager
2024	J	`jnl`	Online Algorithmic Recourse by Collective Action. CoRR Elliot Creager, Richard S. Zemel
2024	A*	`conf`	Out of the Ordinary: Spectrally Adapting Regression for Covariate Shift. ICML Benjamin Eyre, Elliot Creager, David Madras, Vardan Papyan, Richard S. Zemel
2024	J	`jnl`	Promoting User Data Autonomy During the Dissolution of a Monopolistic Firm. CoRR Rushabh Solanki, Elliot Creager
2024	A*	`conf`	Remembering to Be Fair: Non-Markovian Fairness in Sequential Decision Making. ICML Parand A. Alamdari, Toryn Q. Klassen, Elliot Creager, Sheila A. McIlraith
2024	J	`jnl`	Show, Don't Tell: Uncovering Implicit Character Portrayal using LLMs. CoRR Brandon Jaipersaud, Zining Zhu, Frank Rudzicz, Elliot Creager
2023	J	`jnl`	Out of the Ordinary: Spectrally Adapting Regression for Covariate Shift. CoRR Benjamin Eyre, Elliot Creager, David Madras, Vardan Papyan, Richard S. Zemel
2023	J	`jnl`	Remembering to Be Fair: On Non-Markovian Fairness in Sequential Decision Making (Preliminary Report). CoRR Parand Alizadeh Alamdari, Toryn Q. Klassen, Elliot Creager, Sheila A. McIlraith
2023	—	`—`	Robust Machine Learning by Transforming and Augmenting Imperfect Training Data Elliot Creager
2023	J	`jnl`	Robust Machine Learning by Transforming and Augmenting Imperfect Training Data. CoRR Elliot Creager
2023	J	`jnl`	SURFSUP: Learning Fluid Simulation for Novel Surfaces. CoRR Arjun Mani, Ishaan Preetam Chandratreya, Elliot Creager, Carl Vondrick, Richard S. Zemel
2023	A*	`conf`	SurfsUp: Learning Fluid Simulation for Novel Surfaces. ICCV Arjun Mani, Ishaan Preetam Chandratreya, Elliot Creager, Carl Vondrick, Richard S. Zemel
2022	A*	`conf`	MoCoDA: Model-based Counterfactual Data Augmentation. NeurIPS Silviu Pitis, Elliot Creager, Ajay Mandlekar, Animesh Garg
2022	J	`jnl`	MoCoDA: Model-based Counterfactual Data Augmentation. CoRR Silviu Pitis, Elliot Creager, Ajay Mandlekar, Animesh Garg
2021	A*	`conf`	Environment Inference for Invariant Learning. ICML Elliot Creager, Jörn-Henrik Jacobsen, Richard S. Zemel
2021	A*	`conf`	On Disentangled Representations Learned from Correlated Data. ICML Frederik Träuble, Elliot Creager, Niki Kilbertus, Francesco Locatello, Andrea Dittadi, Anirudh Goyal, Bernhard Schölkopf, Stefan Bauer
2020	A*	`conf`	Causal Modeling for Fairness In Dynamical Systems. ICML Elliot Creager, David Madras, Toniann Pitassi, Richard S. Zemel
2020	A*	`conf`	Counterfactual Data Augmentation using Locally Factored Dynamics. NeurIPS Silviu Pitis, Elliot Creager, Animesh Garg
2020	J	`jnl`	Counterfactual Data Augmentation using Locally Factored Dynamics. CoRR Silviu Pitis, Elliot Creager, Animesh Garg
2020	J	`jnl`	Exchanging Lessons Between Algorithmic Fairness and Domain Generalization. CoRR Elliot Creager, Jörn-Henrik Jacobsen, Richard S. Zemel
2020	J	`jnl`	Fairness and Robustness in Invariant Learning: A Case Study in Toxicity Classification. CoRR Robert Adragna, Elliot Creager, David Madras, Richard S. Zemel
2020	J	`jnl`	Is Independence all you need? On the Generalization of Representations Learned from Correlated Data. CoRR Frederik Träuble, Elliot Creager, Niki Kilbertus, Anirudh Goyal, Francesco Locatello, Bernhard Schölkopf, Stefan Bauer
2020	A*	`conf`	Optimizing Long-term Social Welfare in Recommender Systems: A Constrained Matching Approach. ICML Martin Mladenov, Elliot Creager, Omer Ben-Porat, Kevin Swersky, Richard S. Zemel, Craig Boutilier
2020	J	`jnl`	Optimizing Long-term Social Welfare in Recommender Systems: A Constrained Matching Approach. CoRR Martin Mladenov, Elliot Creager, Omer Ben-Porat, Kevin Swersky, Richard S. Zemel, Craig Boutilier
2019	J	`jnl`	Causal Modeling for Fairness in Dynamical Systems. CoRR Elliot Creager, David Madras, Toniann Pitassi, Richard S. Zemel
2019	—	`conf`	Explaining Image Classifiers by Counterfactual Generation. ICLR (Poster) Chun-Hao Chang, Elliot Creager, Anna Goldenberg, David Duvenaud
2019	—	`conf`	Fairness through Causal Awareness: Learning Causal Latent-Variable Models for Biased Data. FAT David Madras, Elliot Creager, Toniann Pitassi, Richard S. Zemel
2019	A*	`conf`	Flexibly Fair Representation Learning by Disentanglement. ICML Elliot Creager, David Madras, Jörn-Henrik Jacobsen, Marissa A. Weis, Kevin Swersky, Toniann Pitassi, Richard S. Zemel
2019	J	`jnl`	Flexibly Fair Representation Learning by Disentanglement. CoRR Elliot Creager, David Madras, Jörn-Henrik Jacobsen, Marissa A. Weis, Kevin Swersky, Toniann Pitassi, Richard S. Zemel
2018	J	`jnl`	Explaining Image Classifiers by Adaptive Dropout and Generative In-filling. CoRR Chun-Hao Chang, Elliot Creager, Anna Goldenberg, David Duvenaud
2018	J	`jnl`	Fairness Through Causal Awareness: Learning Latent-Variable Models for Biased Data. CoRR David Madras, Elliot Creager, Toniann Pitassi, Richard S. Zemel
2018	—	`conf`	Gradient-based Optimization of Neural Network Architecture. ICLR (Workshop) Will Grathwohl, Elliot Creager, Seyed Kamyar Seyed Ghasemipour, Richard S. Zemel
2018	A*	`conf`	Learning Adversarially Fair and Transferable Representations. ICML David Madras, Elliot Creager, Toniann Pitassi, Richard S. Zemel
2018	J	`jnl`	Learning Adversarially Fair and Transferable Representations. CoRR David Madras, Elliot Creager, Toniann Pitassi, Richard S. Zemel
2016	—	`conf`	Nonnegative Tensor Factorization with Frequency Modulation Cues for Blind Audio Source Separation. ISMIR Elliot Creager, Noah D. Stein, Roland Badeau, Philippe Depalle
2016	J	`jnl`	Nonnegative tensor factorization with frequency modulation cues for blind audio source separation. CoRR Elliot Creager, Noah D. Stein, Roland Badeau, Philippe Depalle