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Workshop: Advances in Programming Languages and Neurosymbolic Systems (AIPLANS)

Towards Neural Functional Program Evaluation

Torsten Scholak · Jonathan Pilault


This paper explores the capabilities of current transformer-based language models for program evaluation of simple functional programming languages. We introduce a new program generation mechanism that allows control over syntactic sugar for semantically equivalent programs. T5 experiments reveal that neural functional program evaluation performs surprisingly well, achieving high 90% exact program match scores for most in-distribution and out-of-distribution tests. We present and evaluate on three datasets to study generalization abilities that are specific to functional programs based on: type, function composition, and reduction steps.