| 2024 | ACL | An Experimental Design Framework for Label-Efficient Supervised Finetuning of Large Language Models. | Gantavya Bhatt, Yifang Chen, Arnav Mohanty Das, Jifan Zhang, Sang T. Truong, Stephen Mussmann, Yinglun Zhu, Jeff A. Bilmes, Simon S. Du, Kevin Jamieson, Jordan T. Ash, Robert D. Nowak |
| 2021 | AISTATS | Comparing the Value of Labeled and Unlabeled Data in Method-of-Moments Latent Variable Estimation. | Mayee F. Chen, Benjamin Cohen-Wang, Stephen Mussmann, Frederic Sala, Christopher R |
| 2020 | EMNLP | On the Importance of Adaptive Data Collection for Extremely Imbalanced Pairwise Tasks. | Stephen Mussmann, Robin Jia, Percy Liang |
| 2020 | ICLR | Selection via Proxy: Efficient Data Selection for Deep Learning. | Cody Coleman, Christopher Yeh, Stephen Mussmann, Baharan Mirzasoleiman, Peter Bailis, Percy Liang, Jure Leskovec, Matei Zaharia |
| 2020 | ICML | Concept Bottleneck Models. | Pang Wei Koh, Thao Nguyen, Yew Siang Tang, Stephen Mussmann, Emma Pierson, Been Kim, Percy Liang |
| 2020 | SODA | A Tight Analysis of Greedy Yields Subexponential Time Approximation for Uniform Decision Tree. | Ray Li, Percy Liang, Stephen Mussmann |
| 2018 | ACL | The price of debiasing automatic metrics in natural language evalaution. | Arun Tejasvi Chaganty, Stephen Mussmann, Percy Liang |
| 2018 | AISTATS | Generalized Binary Search For Split-Neighborly Problems. | Stephen Mussmann, Percy Liang |
| 2018 | ICML | On the Relationship between Data Efficiency and Error for Uncertainty Sampling. | Stephen Mussmann, Percy Liang |
| 2017 | UAI | Fast Amortized Inference and Learning in Log-linear Models with Randomly Perturbed Nearest Neighbor Search. | Stephen Mussmann, Daniel Levy, Stefano Ermon |
| 2016 | ICML | Learning and Inference via Maximum Inner Product Search. | Stephen Mussmann, Stefano Ermon |
| 2015 | AAAI | Incorporating Assortativity and Degree Dependence into Scalable Network Models. | Stephen Mussmann, John Moore, Joseph John Pfeiffer III, Jennifer Neville |
| 2014 | KDD | Assortativity in Chung Lu Random Graph Models. | Stephen Mussmann, John Moore, Joseph J. Pfeiffer III, Jennifer Neville |