OpenFlamingo: An Open-Source Framework for Training Large Autoregressive Vision-Language Models.
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CoRR, 2023
Out-of-Domain Robustness via Targeted Augmentations.
Proceedings of the International Conference on Machine Learning, 2023
How does a small molecule bind at a cryptic binding site?
PLoS Comput. Biol., 2022
Extending the WILDS Benchmark for Unsupervised Adaptation.
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Proceedings of the Tenth International Conference on Learning Representations, 2022
Accuracy on the Line: on the Strong Correlation Between Out-of-Distribution and In-Distribution Generalization.
Proceedings of the 38th International Conference on Machine Learning, 2021
Just Train Twice: Improving Group Robustness without Training Group Information.
Proceedings of the 38th International Conference on Machine Learning, 2021
WILDS: A Benchmark of in-the-Wild Distribution Shifts.
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Proceedings of the 38th International Conference on Machine Learning, 2021
Selective Classification Can Magnify Disparities Across Groups.
Proceedings of the 9th International Conference on Learning Representations, 2021
An Investigation of Why Overparameterization Exacerbates Spurious Correlations.
Proceedings of the 37th International Conference on Machine Learning, 2020
Distributionally Robust Neural Networks.
Proceedings of the 8th International Conference on Learning Representations, 2020
Distributionally Robust Neural Networks for Group Shifts: On the Importance of Regularization for Worst-Case Generalization.
CoRR, 2019
Multi-Resolution Weak Supervision for Sequential Data.
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Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019
Distributionally Robust Language Modeling.
Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing, 2019