How to Train Your AI PA: A Novel Approach to Timeline Evaluation and Inference
Abstract
We address the issue of timeline evaluation and inference on timeline models. We develop an exciting new framework for evaluation, and argue for its theoretical soundness. We also improve upon the state-of-the-art in terms of model inference. We make the first attempts in the literature to apply variational inference methods to the timeline generation problem. In doing so we obtain results that are competitive in terms of the timelines generated with speed-ups of an order of magnitude.