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ZENODO
Report . 2026
License: CC BY
Data sources: ZENODO
ZENODO
Report . 2026
License: CC BY
Data sources: Datacite
ZENODO
Report . 2026
License: CC BY
Data sources: Datacite
addClaim

Llama-3.1-8B Performance on MBPP Against Open-Source 8B-Parameter Models CodeMixBench: Evaluating LLM Robustness on Multilingual Code-Mixing Tasks

Authors: Assignee Research;

Llama-3.1-8B Performance on MBPP Against Open-Source 8B-Parameter Models CodeMixBench: Evaluating LLM Robustness on Multilingual Code-Mixing Tasks

Abstract

This report synthesises findings from 2 peer-reviewed papers addressing the following research question: How does Llama-3.1-8B's performance on MBPP compare to other open-source 8B-parameter models like Falcon-8B or Mistral-8B in terms of pass@1 accuracy. Large Language Models (LLMs) have achieved remarkable success in code generation tasks, powering various applications like code completion, debugging, and programming assistance. However, existing benchmarks such as HumanEval, MBPP, and BigCodeBench primarily evaluate LLMs on. 7 claims were extracted from source literature; 6 were independently verified against retrieved documents. An automated multi-reviewer quality assessment produced a score of 7.9/10. This report is a machine-generated literature synthesis and does not constitute original research. Research goal: How does Llama-3.1-8B's performance on MBPP compare to other open-source 8B-parameter models like Falcon-8B or Mistral-8B in terms of pass@1 accuracy? Autonomous literature synthesis. Automated review score: 7.9/10. Full text and citation available at Assignee Research.

Machine-generated literature synthesis. Content is derived from peer-reviewed papers; see individual sources for authoritative data. Automated review score: 7.9/10. Published by Assignee Research (https://assignee.net).

Keywords

models, Llama-3, parameter, like, other, MBPP, performance, open-source

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    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average