Correlation Between Parameter Scale and Robustness Against Adversarial Syntactic Perturbations in Arabic Code Generation

Abstract

Abstract: We introduce self-invoking code generation, a new task designed to evaluate the progressive reasoning and problem-solving capabilities of LLMs. In this task, models are presented with a base problem and a related, more complex problem. They must solve the base problem and then utilize its solution to address the more complex one. This work features three key contributions. First, we propose a general recipe for generating more challenging versions of existing benchmarks, resulting in three new benchmarks: HumanEval Pro, MBPP Pro, and BigCodeBench-Lite Pro, specifically designed to assess LLMs

Research Question

How does increasing parameter scale correlate with robustness against adversarial syntactic perturbations in Arabic code generation tasks within the MBPP Pro benchmark?

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Correction Record

Public corrections are additive records. Current status does not claim the synthesis is error-free.

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