- author = "Alberto Moraglio and Alberto Tonda",
- title = "Language Model-Driven Program Synthesis with Program Trace Optimization on the Abstraction and Reasoning Corpus",
- booktitle = "Genetic Programming Theory and Practice XXII",
- year = "2025",
- editor = "Bogdan Burlacu and Fabricio {Olivetti de Franca} and Alexander Lalejini and Stephen Kelly and Wolfgang Banzhaf",
- series = "Genetic and Evolutionary Computation",
- pages = "211--232",
- address = "Michigan State University, USA",
- month = jun # " 5-7",
- publisher = "Springer",
- keywords = "genetic algorithms, genetic programming, ANN, LLM, AI, PTO",
- isbn13 = "978-981-95-6397-5",
-
DOI = "
10.1007/978-981-95-6398-2_11",
- abstract = "a generator that creates candidate solutions, and a fitness function that evaluates them. This framework enables any search algorithm to be applied to any problem through a universal trace representation. A key strength of PTO is its ability to work with unrestricted programs as generators. While PTO has traditionally been used with simple random solution generators, we explore its application to more sophisticated generators based on language models. Using the Abstraction and Reasoning Corpus (ARC) as our case study, we show how PTO can effectively search the space of programs generated by language models trained on domain-specific languages. This demonstrates how PTO trace-based framework can guide the search through the space of programs, while harnessing the learned patterns and structure captured by the language model. Our work exemplifies how PTO can seamlessly extend beyond conventional evolutionary computation boundaries by incorporating advanced generative methods without requiring modification.",
-
notes = "lightning talk.
published in 2026 after the workshop",
