Machine learning research communication via illustrated and interactive web articles

J Alammar

Keywords: exposition, explanation, reserach communication, research software, natural language processing

Abstract: The recent explosion in machine learning research activity poses challenges for both researchers who aim to widely disseminate their work, as well as to readers who find it challenging to keep up with the onslaught of new research ideas. In this paper, we describe a workflow for creating a spectrum of machine learning research communication artifacts optimized to maximize the clarity of scientific communication, advance the fronts of explainability and interpretability, as well as empower the community to reproduce research software. The workflow describes creating a spectrum of communication artifacts including visuals, animations, interactive explorables, reproducible notebooks, open-source software, and software packages. The articles produced by this workflow have explained cutting-edge-ML research to a large audience and were read over three million times.