Multi-hop reasoning for HowTo questions

Bachelor Thesis, Master Thesis

Recently, large pre-trained language models have shown great success on a variety of applications in NLP. Using these models, it has already been shown, that it is possible to find the correct answer to questions, that require reasoning over multiple sentences of the input text. Preferably, however, we would like to have computer systems, that are able to aggregate different information on their own in a meaningful ways, that help people with their problems. In this thesis we like to investigate, how well models can reason over the (causal) implications of multiple steps of HowTo instructions from WikiHow. Specifically, we want to investigate, how well language models are able to re-construct the order (when required) of multiple step-wise instructions, leading to a specific goal (e.g. “How to build a house?”)