The Whiting School of Engineering has compiled a list of resource guides, worksheets, training, articles, books, and media related to unconscious bias, interrupting bias, allyship, and the history of race in the U.S.
Information for the Whiting School community about prevention and preparedness efforts at Johns Hopkins and around the world. Includes important information for current and prospective/newly admitted Johns Hopkins Engineering graduate students and postdoctoral fellows.
Abstract Transformers are essential to pretraining. As we approach 5 years of BERT, the connection between attention as architecture and transfer learning remains key to this central thread in NLP. Other architectures such as CNNs and RNNs[...]
Abstract While large language models have advanced the state-of-the-art in natural language processing, these models are trained on large-scale datasets, which may include harmful information. Studies have shown that as a result, the models exhibit[...]
Abstract Advanced neural language models have grown ever larger and more complex, pushing forward the limits of language understanding and generation, while diminishing interpretability. The black-box nature of deep neural networks blocks humans from understanding[...]
Abstract Understanding the implications underlying a text is critical to assessing its impact, in particular the social dynamics that may result from a reading of the text. This requires endowing artificial intelligence (AI) systems with[...]