Ratner, Alexander

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

AMELIE speeds Mendelian diagnosis by matching patient phenotype and genotype to primary literature

Birgmeier, J., Haeussler, M., Deisseroth, C. A., Steinberg, E. H., Jagadeesh, K. A., Ratner, A. J., Guturu, H., Wenger, A. M., Diekhans, M. E., Stenson, P. D., et al. (2020) · Science Translational Medicine

Genomics and Rare DiseasesBiomedical Text Mining and Ontologies

Cited by 118

Found in the middle: Calibrating Positional Attention Bias Improves Long Context Utilization

Hsieh, C.-Y., Chuang, Y.-S., Li, C.-L., Wang, Z., Le, L., Kumar, A., Glass, J., Ratner, A., Lee, C.-Y., Krishna, R., et al. (2024) · Findings of the Association for Computational Linguistics ACL 2024

Topic ModelingNatural Language Processing Techniques

Cited by 31

Distilling Step-by-Step! Outperforming Larger Language Models with Less Training Data and Smaller Model Sizes

Hsieh, C.-Y., Li, C.-L., Yeh, C.-K., Nakhost, H., Fujii, Y., Ratner, A., Krishna, R., Lee, C.-Y., & Pfister, T. (2023) · arXiv

Topic ModelingDomain Adaptation and Few-Shot Learning

Cited by 16

Found in the Middle: Calibrating Positional Attention Bias Improves Long Context Utilization

Hsieh, C.-Y., Chuang, Y.-S., Li, C.-L., Wang, Z., Le, L. T., Kumar, A., Glass, J., Ratner, A., Lee, C.-Y., Krishna, R., et al. (2024) · arXiv

Topic ModelingMultimodal Machine Learning Applications

Cited by 0