Reviews: Backpropagation with Callbacks: Foundations for Efficient and Expressive Differentiable Programming

The paper descries Lantern, a framework for automatic differentiation in Scala, based on callbacks and continuation passing style. It compares against PyTorch and TensorFlow on several benchmark tasks. There are two main aspects of the paper: Reverse-mode automatic differentiation with continuations, and code generation via multi-stage programming. The submission does not provide code for the proposed framework, which I don't find acceptable for a paper on a software package. It's unclear to me how the first is different from any other implementation of automatic differentiation via operator overloading.