Sang Michael Xie

According to our database, Sang Michael Xie authored at least 24 papers between 2016 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

A Survey on Data Selection for Language Models.

Alon Albalak, Yanai Elazar, Sang Michael Xie, Shayne Longpre, Nathan Lambert, Xinyi Wang, Niklas Muennighoff, Bairu Hou, Liangming Pan, Haewon Jeong, Colin Raffel, Shiyu Chang, Tatsunori Hashimoto, William Yang Wang

CoRR, 2024

Connect Later: Improving Fine-tuning for Robustness with Targeted Augmentations.

Helen Qu, Sang Michael Xie

CoRR, 2024

2023

Data Selection for Language Models via Importance Resampling.

Sang Michael Xie, Shibani Santurkar, Tengyu Ma, Percy Liang

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

DoReMi: Optimizing Data Mixtures Speeds Up Language Model Pretraining.

Sang Michael Xie, Hieu Pham, Xuanyi Dong, Nan Du, Hanxiao Liu, Yifeng Lu, Percy Liang, Quoc V. Le, Tengyu Ma, Adams Wei Yu

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Same Pre-training Loss, Better Downstream: Implicit Bias Matters for Language Models.

Hong Liu, Sang Michael Xie, Zhiyuan Li, Tengyu Ma

Proceedings of the International Conference on Machine Learning, 2023

Reward Design with Language Models.

Minae Kwon, Sang Michael Xie, Kalesha Bullard, Dorsa Sadigh

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

Holistic Evaluation of Language Models.

Percy Liang, Rishi Bommasani, Tony Lee, Dimitris Tsipras, Dilara Soylu, Michihiro Yasunaga, Yian Zhang, Deepak Narayanan, Yuhuai Wu, Ananya Kumar, Benjamin Newman, Binhang Yuan, Bobby Yan, Ce Zhang, Christian Cosgrove, Christopher D. Manning, Christopher Ré, Diana Acosta-Navas, Drew A. Hudson, Eric Zelikman, Esin Durmus, Faisal Ladhak, Frieda Rong, Hongyu Ren, Huaxiu Yao, Jue Wang, Keshav Santhanam, Laurel J. Orr, Lucia Zheng, Mert Yüksekgönül, Mirac Suzgun, Nathan Kim, Neel Guha, Niladri S. Chatterji, Omar Khattab, Peter Henderson, Qian Huang, Ryan Chi, Sang Michael Xie, Shibani Santurkar, Surya Ganguli, Tatsunori Hashimoto, Thomas Icard, Tianyi Zhang, Vishrav Chaudhary, William Wang, Xuechen Li, Yifan Mai, Yuhui Zhang, Yuta Koreeda

CoRR, 2022

Connect, Not Collapse: Explaining Contrastive Learning for Unsupervised Domain Adaptation.

Kendrick Shen, Robbie M. Jones, Ananya Kumar, Sang Michael Xie, Jeff Z. HaoChen, Tengyu Ma, Percy Liang

Proceedings of the International Conference on Machine Learning, 2022

An Explanation of In-context Learning as Implicit Bayesian Inference.

Sang Michael Xie, Aditi Raghunathan, Percy Liang, Tengyu Ma

Proceedings of the Tenth International Conference on Learning Representations, 2022

Extending the WILDS Benchmark for Unsupervised Adaptation.

Shiori Sagawa, Pang Wei Koh, Tony Lee, Irena Gao, Sang Michael Xie, Kendrick Shen, Ananya Kumar, Weihua Hu, Michihiro Yasunaga, Henrik Marklund, Sara Beery, Etienne David, Ian Stavness, Wei Guo, Jure Leskovec, Kate Saenko, Tatsunori Hashimoto, Sergey Levine, Chelsea Finn, Percy Liang

Proceedings of the Tenth International Conference on Learning Representations, 2022

2021

No True State-of-the-Art? OOD Detection Methods are Inconsistent across Datasets.

Fahim Tajwar, Ananya Kumar, Sang Michael Xie, Percy Liang

CoRR, 2021

Why Do Pretrained Language Models Help in Downstream Tasks? An Analysis of Head and Prompt Tuning.

Colin Wei, Sang Michael Xie, Tengyu Ma

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Composed Fine-Tuning: Freezing Pre-Trained Denoising Autoencoders for Improved Generalization.

Sang Michael Xie, Tengyu Ma, Percy Liang

Proceedings of the 38th International Conference on Machine Learning, 2021

WILDS: A Benchmark of in-the-Wild Distribution Shifts.

Pang Wei Koh, Shiori Sagawa, Henrik Marklund, Sang Michael Xie, Marvin Zhang, Akshay Balsubramani, Weihua Hu, Michihiro Yasunaga, Richard Lanas Phillips, Irena Gao, Tony Lee, Etienne David, Ian Stavness, Wei Guo, Berton Earnshaw, Imran S. Haque, Sara M. Beery, Jure Leskovec, Anshul Kundaje, Emma Pierson, Sergey Levine, Chelsea Finn, Percy Liang

Proceedings of the 38th International Conference on Machine Learning, 2021

In-N-Out: Pre-Training and Self-Training using Auxiliary Information for Out-of-Distribution Robustness.

Sang Michael Xie, Ananya Kumar, Robbie Jones, Fereshte Khani, Tengyu Ma, Percy Liang

Proceedings of the 9th International Conference on Learning Representations, 2021

2020

Weakly Supervised Deep Learning for Segmentation of Remote Sensing Imagery.

Sherrie Wang, William Chen, Sang Michael Xie, George Azzari, David B. Lobell

Remote. Sens., 2020

WILDS: A Benchmark of in-the-Wild Distribution Shifts.

Pang Wei Koh, Shiori Sagawa, Henrik Marklund, Sang Michael Xie, Marvin Zhang, Akshay Balsubramani, Weihua Hu, Michihiro Yasunaga, Richard Lanas Phillips, Sara Beery, Jure Leskovec, Anshul Kundaje, Emma Pierson, Sergey Levine, Chelsea Finn, Percy Liang

CoRR, 2020

Simplifying Models with Unlabeled Output Data.

Sang Michael Xie, Tengyu Ma, Percy Liang

CoRR, 2020

Understanding and Mitigating the Tradeoff between Robustness and Accuracy.

Aditi Raghunathan, Sang Michael Xie, Fanny Yang, John C. Duchi, Percy Liang

Proceedings of the 37th International Conference on Machine Learning, 2020

2019

Adversarial Training Can Hurt Generalization.

Aditi Raghunathan, Sang Michael Xie, Fanny Yang, John C. Duchi, Percy Liang

CoRR, 2019

Differentiable Subset Sampling.

Sang Michael Xie, Stefano Ermon

CoRR, 2019

Reparameterizable Subset Sampling via Continuous Relaxations.

Sang Michael Xie, Stefano Ermon

Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019

2018

Semi-supervised Deep Kernel Learning: Regression with Unlabeled Data by Minimizing Predictive Variance.

Neal Jean, Sang Michael Xie, Stefano Ermon

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

2016

Transfer Learning from Deep Features for Remote Sensing and Poverty Mapping.

Sang Michael Xie, Neal Jean, Marshall Burke, David B. Lobell, Stefano Ermon

Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, 2016