I study artificial neural network models for natural language understanding, with a focus on building high-quality training and evaluation data and on applying these models to scientific questions in syntax and semantics.
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My lab's software toolkit, jiant, just got a from-scratch rewrite, and we think it's a good starting point for most research on NLU, especially for the kinds of tasks that you see in benchmarks like GLUE, SuperGLUE, and XTREME. It builds on the popular Transformers and Datasets libraries.