HYSYNTH: Context-Free LLM Approximation for Guiding Program Synthesis

#AI #arXiv #GitHub #AI #LanguageModels #ProgramSynthesis #OpenSourceAI #GitHub #arXiv Link to paper: Paper by: Shraddha Barke, Emmanuel Anaya Gonzalez, Saketh Ram Kasibatla, Taylor Berg-Kirkpatrick, Nadia Polikarpova Presentation by team: Explore our AI innovations and solutions tailored for diverse business challenges at The paper “HYSYNTH: Context-Free LLM Approximation for Guiding Program Synthesis“ presents a novel hybrid approach combining large language models (LLMs) and symbolic methods to tackle program synthesis challenges. This method uses LLM completions to learn a task-specific, context-free surrogate model, significantly enhancing the synthesis process across various domains. By outperforming both unguided search and direct sampling from LLMs, as well as existing program synthesizers, the research establishes a promising direction for scalable and efficie