Xie, Sang Michael

23 publications

TMLR 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

ICML 2024 Connect Later: Improving Fine-Tuning for Robustness with Targeted Augmentations Helen Qu, Sang Michael Xie

ICMLW 2024 Meta-Designing Quantum Experiments with Language Models Sören Arlt, Haonan Duan, Felix Li, Sang Michael Xie, Yuhuai Wu, Mario Krenn

NeurIPSW 2023 Connect Later: Improving Fine-Tuning for Robustness with Targeted Augmentations Helen Qu, Sang Michael Xie

NeurIPS 2023 Data Selection for Language Models via Importance Resampling Sang Michael Xie, Shibani Santurkar, Tengyu Ma, Percy Liang

NeurIPS 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

TMLR 2023 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 Re, Diana Acosta-Navas, Drew A. Hudson, Eric Zelikman, Esin Durmus, Faisal Ladhak, Frieda Rong, Hongyu Ren, Huaxiu Yao, Jue Wang, Keshav Santhanam, Laurel Orr, Lucia Zheng, Mert Yuksekgonul, Mirac Suzgun, Nathan Kim, Neel Guha, Niladri S. Chatterji, Omar Khattab, Peter Henderson, Qian Huang, Ryan Andrew 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

ICLR 2023 Reward Design with Language Models Minae Kwon, Sang Michael Xie, Kalesha Bullard, Dorsa Sadigh

ICML 2023 Same Pre-Training Loss, Better Downstream: Implicit Bias Matters for Language Models Hong Liu, Sang Michael Xie, Zhiyuan Li, Tengyu Ma

ICLR 2022 An Explanation of In-Context Learning as Implicit Bayesian Inference Sang Michael Xie, Aditi Raghunathan, Percy Liang, Tengyu Ma

ICML 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

ICLR 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

ICML 2021 Composed Fine-Tuning: Freezing Pre-Trained Denoising Autoencoders for Improved Generalization Sang Michael Xie, Tengyu Ma, Percy Liang

NeurIPSW 2021 Ensembles and Cocktails: Robust Finetuning for Natural Language Generation John Hewitt, Xiang Lisa Li, Sang Michael Xie, Benjamin Newman, Percy Liang

NeurIPSW 2021 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

NeurIPSW 2021 How Does Contrastive Pre-Training Connect Disparate Domains? Kendrick Shen, Robbie Matthew Jones, Ananya Kumar, Sang Michael Xie, Percy Liang

ICLR 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

NeurIPS 2021 Why Do Pretrained Language Models Help in Downstream Tasks? an Analysis of Head and Prompt Tuning Colin Wei, Sang Michael Xie, Tengyu Ma

ICML 2020 Understanding and Mitigating the Tradeoff Between Robustness and Accuracy Aditi Raghunathan, Sang Michael Xie, Fanny Yang, John Duchi, Percy Liang

ICMLW 2019 Adversarial Training Can Hurt Generalization Aditi Raghunathan, Sang Michael Xie, Fanny Yang, John Duchi, Percy Liang

IJCAI 2019 Reparameterizable Subset Sampling via Continuous Relaxations Sang Michael Xie, Stefano Ermon

NeurIPS 2018 Semi-Supervised Deep Kernel Learning: Regression with Unlabeled Data by Minimizing Predictive Variance Neal Jean, Sang Michael Xie, Stefano Ermon

AAAI 2016 Transfer Learning from Deep Features for Remote Sensing and Poverty Mapping Sang Michael Xie, Neal Jean, Marshall Burke, David B. Lobell, Stefano Ermon