Towards Understanding What Code Language Models Learned

no code implementations • 20 Jun 2023 • Toufique Ahmed, Dian Yu, Chengxuan Huang, Cathy Wang, Prem Devanbu, Kenji Sagae

To understand the extent to which language models can learn some form of meaning, we investigate their ability to capture semantics of code beyond superficial frequency and co-occurrence.

Using Machine Learning and Natural Language Processing to Review and Classify the Medical Literature on Cancer Susceptibility Genes

no code implementations • 24 Apr 2019 • Yujia Bao, Zhengyi Deng, Yan Wang, Heeyoon Kim, Victor Diego Armengol, Francisco Acevedo, Nofal Ouardaoui, Cathy Wang, Giovanni Parmigiani, Regina Barzilay, Danielle Braun, Kevin S. Hughes

We developed and evaluated two machine learning models to classify abstracts as relevant to the penetrance (risk of cancer for germline mutation carriers) or prevalence of germline genetic mutations.

Classification General Classification