Graph Representations for Higher-Order Logic and Theorem Proving

24 May 2019Aditya PaliwalSarah LoosMarkus RabeKshitij BansalChristian Szegedy

This paper presents the first use of graph neural networks (GNNs) for higher-order proof search and demonstrates that GNNs can improve upon state-of-the-art results in this domain. Interactive, higher-order theorem provers allow for the formalization of most mathematical theories and have been shown to pose a significant challenge for deep learning... (read more)

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TASK DATASET MODEL METRIC NAME METRIC VALUE GLOBAL RANK RESULT LEADERBOARD
Automated Theorem Proving HOList benchmark 4-hop GNN, sub-expression sharing Percentage correct 48.06 # 1

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