Sang Michael Xie

42 papers A* 16Journal 26

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Reuse your FLOPs: Scaling RL on Hard Problems by Conditioning on Very Off-Policy Prefixes. CoRR Amrith Setlur, Zijian Wang, Andrew Cohen, Paria Rashidinejad, Sang Michael Xie
2025	J	`jnl`	Impact of Pretraining Word Co-occurrence on Compositional Generalization in Multimodal Models. CoRR Helen Qu, Sang Michael Xie
2024	J	`jnl`	A Survey on Data Selection for Language Models. CoRR 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
2024	J	`jnl`	A Survey on Data Selection for Language Models. Trans. Mach. Learn. Res. 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
2024	A*	`conf`	Connect Later: Improving Fine-tuning for Robustness with Targeted Augmentations. ICML Helen Qu, Sang Michael Xie
2024	J	`jnl`	Connect Later: Improving Fine-tuning for Robustness with Targeted Augmentations. CoRR Helen Qu, Sang Michael Xie
2024	J	`jnl`	Meta-Designing Quantum Experiments with Language Models. CoRR Sören Arlt, Haonan Duan, Felix Li, Sang Michael Xie, Yuhuai Wu, Mario Krenn
2023	A*	`conf`	Data Selection for Language Models via Importance Resampling. NeurIPS Sang Michael Xie, Shibani Santurkar, Tengyu Ma, Percy Liang
2023	J	`jnl`	Data Selection for Language Models via Importance Resampling. CoRR Sang Michael Xie, Shibani Santurkar, Tengyu Ma, Percy Liang
2023	A*	`conf`	DoReMi: Optimizing Data Mixtures Speeds Up Language Model Pretraining. NeurIPS Sang Michael Xie, Hieu Pham, Xuanyi Dong, Nan Du, Hanxiao Liu, Yifeng Lu, Percy Liang, Quoc V. Le, Tengyu Ma, Adams Wei Yu
2023	J	`jnl`	DoReMi: Optimizing Data Mixtures Speeds Up Language Model Pretraining. CoRR Sang Michael Xie, Hieu Pham, Xuanyi Dong, Nan Du, Hanxiao Liu, Yifeng Lu, Percy Liang, Quoc V. Le, Tengyu Ma, Adams Wei Yu
2023	J	`jnl`	Holistic Evaluation of Language Models. Trans. Mach. Learn. Res. 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
2023	A*	`conf`	Reward Design with Language Models. ICLR Minae Kwon, Sang Michael Xie, Kalesha Bullard, Dorsa Sadigh
2023	J	`jnl`	Reward Design with Language Models. CoRR Minae Kwon, Sang Michael Xie, Kalesha Bullard, Dorsa Sadigh
2023	A*	`conf`	Same Pre-training Loss, Better Downstream: Implicit Bias Matters for Language Models. ICML Hong Liu, Sang Michael Xie, Zhiyuan Li, Tengyu Ma
2022	A*	`conf`	An Explanation of In-context Learning as Implicit Bayesian Inference. ICLR Sang Michael Xie, Aditi Raghunathan, Percy Liang, Tengyu Ma
2022	A*	`conf`	Connect, Not Collapse: Explaining Contrastive Learning for Unsupervised Domain Adaptation. ICML Kendrick Shen, Robbie M. Jones, Ananya Kumar, Sang Michael Xie, Jeff Z. HaoChen, Tengyu Ma, Percy Liang
2022	J	`jnl`	Connect, Not Collapse: Explaining Contrastive Learning for Unsupervised Domain Adaptation. CoRR Kendrick Shen, Robbie Jones, Ananya Kumar, Sang Michael Xie, Jeff Z. HaoChen, Tengyu Ma, Percy Liang
2022	A*	`conf`	Extending the WILDS Benchmark for Unsupervised Adaptation. ICLR 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
2022	J	`jnl`	Holistic Evaluation of Language Models. CoRR 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
2022	J	`jnl`	Same Pre-training Loss, Better Downstream: Implicit Bias Matters for Language Models. CoRR Hong Liu, Sang Michael Xie, Zhiyuan Li, Tengyu Ma
2021	J	`jnl`	An Explanation of In-context Learning as Implicit Bayesian Inference. CoRR Sang Michael Xie, Aditi Raghunathan, Percy Liang, Tengyu Ma
2021	A*	`conf`	Composed Fine-Tuning: Freezing Pre-Trained Denoising Autoencoders for Improved Generalization. ICML Sang Michael Xie, Tengyu Ma, Percy Liang
2021	J	`jnl`	Extending the WILDS Benchmark for Unsupervised Adaptation. CoRR 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
2021	A*	`conf`	In-N-Out: Pre-Training and Self-Training using Auxiliary Information for Out-of-Distribution Robustness. ICLR Sang Michael Xie, Ananya Kumar, Robbie Jones, Fereshte Khani, Tengyu Ma, Percy Liang
2021	J	`jnl`	No True State-of-the-Art? OOD Detection Methods are Inconsistent across Datasets. CoRR Fahim Tajwar, Ananya Kumar, Sang Michael Xie, Percy Liang
2021	A*	`conf`	WILDS: A Benchmark of in-the-Wild Distribution Shifts. ICML 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
2021	A*	`conf`	Why Do Pretrained Language Models Help in Downstream Tasks? An Analysis of Head and Prompt Tuning. NeurIPS Colin Wei, Sang Michael Xie, Tengyu Ma
2021	J	`jnl`	Why Do Pretrained Language Models Help in Downstream Tasks? An Analysis of Head and Prompt Tuning. CoRR Colin Wei, Sang Michael Xie, Tengyu Ma
2020	J	`jnl`	In-N-Out: Pre-Training and Self-Training using Auxiliary Information for Out-of-Distribution Robustness. CoRR Sang Michael Xie, Ananya Kumar, Robbie Jones, Fereshte Khani, Tengyu Ma, Percy Liang
2020	J	`jnl`	Simplifying Models with Unlabeled Output Data. CoRR Sang Michael Xie, Tengyu Ma, Percy Liang
2020	J	`jnl`	Understanding and Mitigating the Tradeoff Between Robustness and Accuracy. CoRR Aditi Raghunathan, Sang Michael Xie, Fanny Yang, John C. Duchi, Percy Liang
2020	A*	`conf`	Understanding and Mitigating the Tradeoff between Robustness and Accuracy. ICML Aditi Raghunathan, Sang Michael Xie, Fanny Yang, John C. Duchi, Percy Liang
2020	J	`jnl`	WILDS: A Benchmark of in-the-Wild Distribution Shifts. CoRR 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
2020	J	`jnl`	Weakly Supervised Deep Learning for Segmentation of Remote Sensing Imagery. Remote. Sens. Sherrie Wang, William Chen, Sang Michael Xie, George Azzari, David B. Lobell
2019	J	`jnl`	Adversarial Training Can Hurt Generalization. CoRR Aditi Raghunathan, Sang Michael Xie, Fanny Yang, John C. Duchi, Percy Liang
2019	J	`jnl`	Differentiable Subset Sampling. CoRR Sang Michael Xie, Stefano Ermon
2019	A*	`conf`	Reparameterizable Subset Sampling via Continuous Relaxations. IJCAI Sang Michael Xie, Stefano Ermon
2018	A*	`conf`	Semi-supervised Deep Kernel Learning: Regression with Unlabeled Data by Minimizing Predictive Variance. NeurIPS Neal Jean, Sang Michael Xie, Stefano Ermon
2018	J	`jnl`	Semi-supervised Deep Kernel Learning: Regression with Unlabeled Data by Minimizing Predictive Variance. CoRR Neal Jean, Sang Michael Xie, Stefano Ermon
2016	A*	`conf`	Transfer Learning from Deep Features for Remote Sensing and Poverty Mapping. AAAI Sang Michael Xie, Neal Jean, Marshall Burke, David B. Lobell, Stefano Ermon
2015	J	`jnl`	Transfer Learning from Deep Features for Remote Sensing and Poverty Mapping. CoRR Sang Michael Xie, Neal Jean, Marshall Burke, David B. Lobell, Stefano Ermon