NeuroTactic is a model for theorem proving which leverages graph neural networks to represent the theorem and premises, and applies graph contrastive learning for pre-training. Specifically, premise selection is designed as a pretext task for the graph contrastive learning approach. The learned representations are then used for the downstream task, tactic prediction
Source: Graph Contrastive Pre-training for Effective Theorem ReasoningPaper | Code | Results | Date | Stars |
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