Research at the intersection of machine learning, programming languages, and software
engineering has recently taken important steps in proposing learnable probabilistic models …

Deep Learning (DL) techniques for Natural Language Processing have been evolving
remarkably fast. Recently, the DL advances in language modeling, machine translation, and …

You are holding in your hands… oh, come on, who holds books like this in their hands
anymore? Anyway, you are reading this, and it means that I have managed to release one of …

Abstract Abstract Visual Reasoning (AVR) problems are commonly used to approximate
human intelligence. They test the ability of applying previously gained knowledge …

High-quality computer science education is limited by the difficulty of providing instructor
feedback to students at scale. While this feedback could in principle be automated …

The availability of representative datasets is an essential prerequisite for many successful
artificial intelligence and machine learning models. However, in real life applications these …

To give a high-level summary to current approaches for implementing artificial intelligence
(AI), we explain the key commonalities and major differences between Turing's approach …

While natural language understanding (NLU) is advancing rapidly, today's technology differs
from human-like language understanding in fundamental ways, notably in its inferior …

Motivated by the recent potential of mass customization brought by whole-garment knitting
machines, we introduce the new problem of automatic machine instruction generation using …

The broad landscape of new technologies currently being explored makes the current times
very exciting for computer systems research. The community is actively researching an …