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William Yang I am a 5th-year PhD Computer Science student in the Princeton Visual AI Lab advised by Prof. Olga Russakovsky. Previously, I completed my undergraduate studies at Carnegie Mellon University, where I was advised by Prof. Leila Wehbe and Prof. Robert F. Murphy. My research focuses on understanding, curating, and generating datasets to enable more efficient training of machine learning models. I am especially interested in how we can use large pre-trained models to create synthetic data that unlocks new capabilities in downstream tasks. I am also interested in the properties of datasets that give rise to certain model abilities and in the kinds of data that trigger failures. |
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Selected Publications |
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Beyond Objects: Contextual Synthetic Data Generation for Fine-Grained Classification
William Yang, Xindi Wu, Zhiwei Deng, Esin Tureci, Olga Russakovsky arXiv, 2025 arXiv / code |
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The Impact of Coreset Selection on Spurious Correlations and Group Robustness
Amaya Dharmasiri, William Yang, Polina Kirichenko, Lydia Liu, Olga Russakovsky NeurIPS Datasets and Benchmarks, 2025 arXiv / code |
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What is Dataset Distillation Learning?
William Yang, Ye Zhu, Zhiwei Deng, Olga Russakovsky ICML, 2024 arXiv / code |
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ImageNet-OOD: Deciphering Modern Out-of-Distribution Detection Algorithms
William Yang*, Byron Zhang*, Olga Russakovsky ICLR, 2024 arXiv / code |