Generative models, particularly diffusion models, are becoming ubiquitous and important in a number of fields. However there are many kinds of bias encoded in such models - some due to the choice of training materials, some are regional, and some are inadvertent.In this project we detect the bias, measure it, and create technological solutions to alleviate or reduce it.We will undertake cutting-edge research for generative and foundation models and release an open source toolkit which will have deep impact in this field.Key Responsibilities:
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