Early Career Latinas in STEM: Challenges and Solutions.

Maggie Werner Washburne,Joann Trejo,Ruth Enid Zambrana,Maria Elena Zavala, Alice Martinic,Angelica Riestra,Tracie Delgado, Staci Edwards, Thelma Escobar,Denneal Jamison-McClung,Mariel Vazquez,Iset Vera, Michelle Guerra, Diana I. Marinez, Elma Gonzalez, Raymond L. Rodriguez

Cell（2023）

Cited 0|Views24

Abstract

Mexican, Puerto Rican, and Central American Ancestry (MPRCA) individuals represent 82% of US Latinos. An intergenerational group of MPRCA women and allies met to discuss persistent underrepresentation of MPRCA women in STEM, identifying multi-level challenges and solutions. Implementation of these solutions is important and will benefit MPRCA women and the entire academic community.

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Pretraining has recently greatly promoted the development of natural language processing (NLP)
We show that M6 outperforms the baselines in multimodal downstream tasks, and the large M6 with 10 parameters can reach a better performance
We propose a method called M6 that is able to process information of multiple modalities and perform both single-modal and cross-modal understanding and generation
The model is scaled to large model with 10 billion parameters with sophisticated deployment, and the 10 -parameter M6-large is the largest pretrained model in Chinese
Experimental results show that our proposed M6 outperforms the baseline in a number of downstream tasks concerning both single modality and multiple modalities We will continue the pretraining of extremely large models by increasing data to explore the limit of its performance

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