Coupling Large Language Models with Logic Programming for Robust and General Reasoning from Text (2023.findings-acl)
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| Challenge: | Large language models (LLMs) are robust and general, but their reasoning ability is not at a level to compete with the best models trained for specific natural language reasoning problems. |
| Approach: | They propose to use large language models as a few-shot semantic parser to convert natural language sentences into a logical form that serves as input for answer set programs. |
| Outcome: | The proposed model can handle multiple question-answering tasks without requiring retraining for each new task. |
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