The aim of this WG is to contribute to the field of machine-learning-based methods to improve the efficiency of automated theorem proving systems in terms of further development of techniques for proof guidance and premise selection. Furthemore, the group will explore how and to what extent tasks of computer-assisted reasoning can be extended to proofs that are represented in (controlled) natural languages.