53 citations · 94 across the 10 of their papers we have counts for
3 papers · 1 filter
LILO: Learning Interpretable Libraries by Compressing and Documenting Code
Gabriel Grand, Lionel Wong, Maddy Bowers +4
While large language models (LLMs) now excel at code generation, a key aspect of software development is the art of refactoring: consolidating code into libraries of reusable and r…
LINC: A Neurosymbolic Approach for Logical Reasoning by Combining Language Models with First-Order Logic Provers
Theo X. Olausson, Alex Gu, Benjamin Lipkin +4
Logical reasoning, i.e., deductively inferring the truth value of a conclusion from a set of premises, is an important task for artificial intelligence with wide potential impacts…
Is Self-Repair a Silver Bullet for Code Generation?
Theo X. Olausson, Jeevana Priya Inala, Chenglong Wang +2
Large language models have shown remarkable aptitude in code generation, but still struggle to perform complex tasks. Self-repair -- in which the model debugs and repairs its own c…