Ilharco, Gabriel

Reproducible Scaling Laws for Contrastive Language-Image Learning

Cherti, M., Beaumont, R., Wightman, R., Wortsman, M., Ilharco, G., Gordon, C., Schuhmann, C., Schmidt, L., & Jitsev, J. (2023) · 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Multimodal Machine Learning ApplicationsDomain Adaptation and Few-Shot Learning

Cited by 673

Robust fine-tuning of zero-shot models

Wortsman, M., Ilharco, G., Kim, J. W., Li, M., Kornblith, S., Roelofs, R., Lopes, R. G., Hajishirzi, H., Farhadi, A., Namkoong, H., et al. (2022) · 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Domain Adaptation and Few-Shot LearningAdvanced Neural Network Applications

Cited by 428

Fine-Tuning Pretrained Language Models: Weight Initializations, Data Orders, and Early Stopping

Dodge, J., Ilharco, G., Schwartz, R., Farhadi, A., Hajishirzi, H., & Smith, N. (2020) · arXiv

Topic ModelingDomain Adaptation and Few-Shot Learning

Cited by 412

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

Documenting Large Webtext Corpora: A Case Study on the Colossal Clean Crawled Corpus

Dodge, J., Sap, M., Marasović, A., Agnew, W., Ilharco, G., Groeneveld, D., Mitchell, M., & Gardner, M. (2021) · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing

Natural Language Processing TechniquesTopic Modeling

Cited by 306

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

Editing Models with Task Arithmetic

Ilharco, G., Ribeiro, M. T., Wortsman, M., Gururangan, S., Schmidt, L., Hajishirzi, H., & Farhadi, A. (2022) · arXiv

Domain Adaptation and Few-Shot LearningTopic Modeling

Cited by 66

Contrasting Contrastive Self-Supervised Representation Learning Pipelines

Kotar, K., Ilharco, G., Schmidt, L., Ehsani, K., & Mottaghi, R. (2021) · 2021 IEEE/CVF International Conference on Computer Vision (ICCV)

Domain Adaptation and Few-Shot LearningAdvanced Neural Network Applications

Cited by 28

Exploring The Landscape of Distributional Robustness for Question Answering Models

Awadalla, A., Wortsman, M., Ilharco, G., Min, S., Magnusson, I., Hajishirzi, H., & Schmidt, L. (2022) · arXiv

Topic ModelingAdversarial Robustness in Machine Learning

Cited by 6

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