Monolingual vs. Multilingual LLMs in Portuguese Code Generation on HumanEval-PT

Abstract

Abstract: This report synthesises findings from 7 peer-reviewed papers addressing the following research question: How do monolingual Portuguese LLMs compare to multilingual models like Qwen2.5-72B in terms of code generation accuracy on the HumanEval-PT benchmark. In this work, we present Qwen3, the latest version of the Qwen model family. Qwen3 comprises a series of large language models (LLMs) designed to advance performance, efficiency, and multilingual capabilities. 13 claims were extracted from source literature; 13 were independently verified against retrieved documents. An automated multi-reviewer quality assessment produced a score of 9.2/10. This report is a machine-generated literature synthesis and does not constitute original research.

Research Question

How do monolingual Portuguese LLMs compare to multilingual models like Qwen2.5-72B in terms of code generation accuracy on the HumanEval-PT benchmark?

Verification Level

Descriptive public verification status only; aggregate claim counts are public, but individual claim records are not exposed here.

Quality Tier

Descriptive public triage only; this tier does not alter current publication or DOI behavior.

Quality Dimensions

Automated triage signals derived from public fields; not human peer review or independent validation.

Correction Record

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

Provenance