Carmon, Yair

Model soups: averaging weights of multiple fine-tuned models improves accuracy without increasing inference time

Wortsman, M., Ilharco, G., Gadre, S. Y., Roelofs, R., Gontijo-Lopes, R., Morcos, A. S., Namkoong, H., Farhadi, A., Carmon, Y., Kornblith, S., et al. (2022) · arXiv

Domain Adaptation and Few-Shot LearningAdvanced Neural Network Applications

Cited by 307

DataComp: In search of the next generation of multimodal datasets

Gadre, S. Y., Ilharco, G., Fang, A., Hayase, J., Smyrnis, G., Nguyen, T., Marten, R., Wortsman, M., Ghosh, D., Zhang, J., et al. (2023) · Advances in Neural Information Processing Systems 36

Multimodal Machine Learning ApplicationsImage Retrieval and Classification Techniques

Cited by 120

Accuracy on the Line: On the Strong Correlation Between Out-of-Distribution and In-Distribution Generalization

Miller, J., Taori, R., Raghunathan, A., Sagawa, S., Koh, P. W., Shankar, V., Liang, P., Carmon, Y., & Schmidt, L. (2021) · arXiv

Domain Adaptation and Few-Shot LearningAdversarial Robustness in Machine Learning

Cited by 74

Large-scale methods for distributionally robust optimization

Levy, D., Carmon, Y., Duchi, J. C., & Sidford, A. (2020) · arXiv

Risk and Portfolio OptimizationStochastic Gradient Optimization Techniques

Cited by 52

Language models scale reliably with over-training and on downstream tasks

Gadre, S. Y., Smyrnis, G., Shankar, V., Gururangan, S., Wortsman, M., Shao, R., Mercat, J., Fang, A., Li, J., Keh, S., et al. (2024) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 5