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 BergKirkpatrick, Nadia Polikarpova Presentation by team: Explore our AI innovations and solutions tailored for diverse business challenges at The paper HYSYNTH: ContextFree 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 taskspecific, contextfree 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