With the growing model size of deep neural networks (DNN), deep learning training is increasingly relying on handcrafted search spaces to find efficient parallelization execution plans. However, our ...

We study the ability of state-of-the art models to answer constraint satisfaction queries for information retrieval (e.g., ‘a list of ice cream shops in San Diego’). In the past, such queries were ...