Neural Unification for Logic Reasoning over Natural Language

1 code implementation • Findings (EMNLP) 2021 • Gabriele Picco, Hoang Thanh Lam, Marco Luca Sbodio, Vanessa Lopez Garcia

The RuleTaker approach of (Clark et al., 2020) achieves appealing results both in terms of accuracy and in the ability to generalize, showing that when the model is trained with deep enough queries (at least 3 inference steps), the transformers are able to correctly answer the majority of queries (97. 6%) that require up to 5 inference steps.

Automated Theorem Proving Question Answering