Sang Michael Xie

Получаване на мой собствен потребителски профил

Позовавания

	Всички	От 2019
Позовавания	12021	11573
h-индекс	21	21
i10-индекс	24	24

4900

2450

1225

3675

20172018201920202021202220232024135 226 311 459 803 1674 3404 4841

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14 статии

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Съавтори

Percy LiangAssociate Professor of Computer Science, Stanford UniversityПотвърден имейл адрес: cs.stanford.edu
Stefano ErmonStanford UniversityПотвърден имейл адрес: cs.stanford.edu
Tengyu MAStanford UniversityПотвърден имейл адрес: stanford.edu
Neal JeanPhD, Stanford UniversityПотвърден имейл адрес: stanford.edu
David LobellStanford UniversityПотвърден имейл адрес: stanford.edu
Aditi RaghunathanAssistant professor, Carnegie Mellon UniversityПотвърден имейл адрес: cmu.edu
Marshall BurkeStanford UniversityПотвърден имейл адрес: stanford.edu
Ananya KumarResearch Scientist, OpenAIПотвърден имейл адрес: cs.stanford.edu
Pang Wei KohUniversity of WashingtonПотвърден имейл адрес: cs.washington.edu
Shiori SagawaPhD Student, Stanford UniversityПотвърден имейл адрес: stanford.edu
John DuchiAssociate Professor of Statistics and Electrical Engineering, Stanford UniversityПотвърден имейл адрес: stanford.edu
Fanny YangETH ZurichПотвърден имейл адрес: inf.ethz.ch
Sherrie WangAssistant Professor, MITПотвърден имейл адрес: mit.edu
Minae KwonStanford UniversityПотвърден имейл адрес: stanford.edu
Shibani SanturkarPostdoc, Stanford UniversityПотвърден имейл адрес: stanford.edu
Quoc V. LeResearch Scientist, GoogleПотвърден имейл адрес: stanford.edu
Hieu PhamxAI. Past: AugmentCode, Google Brain.Потвърден имейл адрес: x.ai
Adams Wei YuResearch Scientist, Google DeepMindПотвърден имейл адрес: cs.cmu.edu
Colin WeiStanford UniversityПотвърден имейл адрес: stanford.edu

Следене

Sang Michael Xie

Други именаMichael Xie

PhD Candidate, Stanford University

Потвърден имейл адрес: cs.stanford.edu - Начална страница

Machine Learning Language Models Reliable Machine Learning Computational Sustainability


Заглавие Сортиране по цитати Сортиране по година Сортиране по заглавие	Позовавания Позовавания	Година
On the opportunities and risks of foundation models R Bommasani, DA Hudson, E Adeli, R Altman, S Arora, S von Arx, ... arXiv preprint arXiv:2108.07258, 2021	4276	2021
Combining satellite imagery and machine learning to predict poverty N Jean, M Burke, M Xie, WM Davis, DB Lobell, S Ermon Science 353 (6301), 790-794, 2016	1875	2016
Wilds: A benchmark of in-the-wild distribution shifts PW Koh, S Sagawa, H Marklund, SM Xie, M Zhang, A Balsubramani, ... International conference on machine learning, 5637-5664, 2021	1483	2021
Holistic evaluation of language models P Liang, R Bommasani, T Lee, D Tsipras, D Soylu, M Yasunaga, Y Zhang, ... arXiv preprint arXiv:2211.09110, 2022	1221*	2022
An Explanation of In-context Learning as Implicit Bayesian Inference SM Xie, A Raghunathan, P Liang, T Ma International Conference on Learning Representations (ICLR), 2022	642	2022
Transfer learning from deep features for remote sensing and poverty mapping M Xie, N Jean, M Burke, D Lobell, S Ermon AAAI, 2016	545	2016
Adversarial training can hurt generalization A Raghunathan, SM Xie, F Yang, JC Duchi, P Liang arXiv preprint arXiv:1906.06032, 2019	280	2019
Understanding and mitigating the tradeoff between robustness and accuracy A Raghunathan, SM Xie, F Yang, J Duchi, P Liang International Conference on Machine Learning (ICML), 2020	261	2020
Weakly supervised deep learning for segmentation of remote sensing imagery S Wang, W Chen, SM Xie, G Azzari, DB Lobell Remote Sensing 12 (2), 207, 2020	246	2020
Reward design with language models M Kwon, SM Xie, K Bullard, D Sadigh arXiv preprint arXiv:2303.00001, 2023	195	2023
Extending the wilds benchmark for unsupervised adaptation S Sagawa, PW Koh, T Lee, I Gao, SM Xie, K Shen, A Kumar, W Hu, ... arXiv preprint arXiv:2112.05090, 2021	129	2021
Data selection for language models via importance resampling SM Xie, S Santurkar, T Ma, PS Liang Advances in Neural Information Processing Systems 36, 34201-34227, 2023	126	2023
Doremi: Optimizing data mixtures speeds up language model pretraining SM Xie, H Pham, X Dong, N Du, H Liu, Y Lu, PS Liang, QV Le, T Ma, ... Advances in Neural Information Processing Systems 36, 2023	107	2023
Connect, not collapse: Explaining contrastive learning for unsupervised domain adaptation K Shen, R Jones, A Kumar, SM Xie, JZ HaoChen, T Ma, P Liang arXiv preprint arXiv:2204.00570, 2022	105	2022
Semi-supervised Deep Kernel Learning: Regression with Unlabeled Data by Minimizing Predictive Variance N Jean, SM Xie, S Ermon Advances in Neural Information Processing Systems (NeurIPS), 2018	101	2018
Reparameterizable Subset Sampling via Continuous Relaxations SM Xie, S Ermon IJCAI, 2019	92	2019
Why Do Pretrained Language Models Help in Downstream Tasks? An Analysis of Head and Prompt Tuning C Wei, SM Xie, T Ma Neural Information Processing Systems (NeurIPS), 2021	91	2021
A survey on data selection for language models A Albalak, Y Elazar, SM Xie, S Longpre, N Lambert, X Wang, ... arXiv preprint arXiv:2402.16827, 2024	62	2024
In-N-Out: Pre-Training and Self-Training using Auxiliary Information for Out-of-Distribution Robustness SM Xie, A Kumar, R Jones*, F Khani, T Ma, P Liang International Conference on Learning Representations (ICLR), 2022	61	2022
Same pre-training loss, better downstream: Implicit bias matters for language models H Liu, SM Xie, Z Li, T Ma International Conference on Machine Learning, 22188-22214, 2023	37	2023

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