| Challenge: | Existing models that learn to jointly infer an expression’s syntactic structure and its semantics fail to learn the correct parsing strategy on mathematical expressions generated from a simple context-free grammar. |
| Approach: | They propose a recursive model that learns to jointly infer an expression’s syntactic structure and its semantics without requiring a formal supervision. |
| Outcome: | The proposed model performs competitively on several natural language tasks, such as Natural Language Inference and Sentiment Analysis. |
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