MIT Presents New Approach for Sequence-to-Sequence Learning with Latent Neural Grammars | Synced
A new MIT CSAIL paper presents an alternative, hierarchical approach to sequence-to-sequence learning with quasi-synchronous grammars to improve sequence-to-sequence models’ compositional generaliz...
Source: Synced | AI Technology & Industry Review
A new MIT CSAIL paper presents an alternative, hierarchical approach to sequence-to-sequence learning with quasi-synchronous grammars to improve sequence-to-sequence models’ compositional generalization on diagnostic tasks.