As language models (LMs) improve at tasks like image generation, trivia questions, and simple math, you might think that ...

redun aims to be a more expressive and efficient workflow framework, built on top of the popular Python programming language. It takes the somewhat contrarian view that writing dataflows directly is ...

Abstract: Three-dimensional finite-difference time-domain (FDTD) models of the global Earth-ionosphere waveguide were first introduced in the early 2000s. These models have been applied to a wide ...

Abstract: Text parallelization is a crucial aspect of natural language processing, aiming to enhance the efficiency of information retrieval and analysis. This project focuses on leveraging the Term ...

Welcome to Meridian! Built on a graph-based architecture, Meridian goes beyond simple turn-taking, enabling richer, more nuanced, and highly efficient interactions. Traditional AI chats often struggle ...

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 ...