Pitler, Emily

Gemini: A Family of Highly Capable Multimodal Models

Gemini Team, Anil, R., Borgeaud, S., Alayrac, J.-B., Yu, J., Soricut, R., Schalkwyk, J., Dai, A. M., Hauth, A., Millican, K., et al. (2023) · arXiv

Multimodal Machine Learning ApplicationsTopic Modeling

Cited by 990

Revisiting readability: a unified framework for predicting text quality

Pitler, E., & Nenkova, A. (2008) · Proceedings of the Conference on Empirical Methods in Natural Language Processing - EMNLP '08

Text Readability and SimplificationNatural Language Processing Techniques

Cited by 375

Measuring and Reducing Gendered Correlations in Pre-trained Models

Webster, K., Wang, X., Tenney, I., Beutel, A., Pitler, E., Pavlick, E., Chen, J., Chi, E., & Petrov, S. (2020) · arXiv

Ethics and Social Impacts of AITopic Modeling

Cited by 195

Giving BERT a Calculator: Finding Operations and Arguments with Reading Comprehension

Andor, D., He, L., Lee, K., & Pitler, E. (2019) · Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP)

Topic ModelingNatural Language Processing Techniques

Cited by 72

Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilities

Comanici, G., Bieber, E., Schaekermann, M., Pasupat, I., Sachdeva, N., Dhillon, I., Blistein, M., Ram, O., Zhang, D., Rosen, E., et al. (2025) · arXiv

Multimodal Machine Learning ApplicationsTopic Modeling

Cited by 69