5 papers
HyGenar: An LLM-Driven Hybrid Genetic Algorithm for Few-Shot Grammar Generation
Weizhi Tang, Yixuan Li, Chris Sypherd +2
Grammar plays a critical role in natural language processing and text/code generation by enabling the definition of syntax, the creation of parsers, and guiding structured outputs.…
Guided Tensor Lifting
Yixuan Li, José Wesley de Souza Magalhães, Alexander Brauckmann +2
Domain-specific languages (DSLs) for machine learning are revolutionizing the speed and efficiency of machine learning workloads as they enable users easy access to high-performanc…
Online Prompt Selection for Program Synthesis
Yixuan Li, Lewis Frampton, Federico Mora +1
Large Language Models (LLMs) demonstrate impressive capabilities in the domain of program synthesis. This level of performance is not, however, universal across all tasks, all LLMs…
Guiding Enumerative Program Synthesis with Large Language Models
Yixuan Li, Julian Parsert, Elizabeth Polgreen
Pre-trained Large Language Models (LLMs) are beginning to dominate the discourse around automatic code generation with natural language specifications. In contrast, the best-perfor…
Genetic Algorithms for Searching a Matrix of Metagrammars for Synthesis
Yixuan Li, Federico Mora, Elizabeth Polgreen +1
Syntax-guided synthesis is a paradigm in program synthesis in which the search space of candidate solutions is constrained by a syntactic template in the form of a grammar. These s…