Overcoming the Expressivity-Efficiency Tradeoff in Program Induction
People are incredibly flexible and efficient inductive reasoners. On the other hand, current approaches in program synthesis show strong domain-specific performance, but are both less sample-efficient and less flexible. Large language models improve upon this sample-efficiency and domain-generality,...
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| Format: | Thesis |
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Massachusetts Institute of Technology
2024
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| Online Access: | https://hdl.handle.net/1721.1/156932 |