What is the impact of cross-domain fine-tuning on security-specific code corpora (e.g., CWE datasets) on the i

Abstract

Abstract: The BigCode community, an open-scientific collaboration working on the responsible development of Large Language Models for Code (Code LLMs), introduces StarCoder and StarCoderBase: 15.5B parameter models with 8K context length, infilling capabilities and fast large-batch inference enabled by multi-query attention. StarCoderBase is trained on 1 trillion tokens sourced from The Stack, a large collection of permissively licensed GitHub repositories with inspection tools and an opt-out process. We fine-tuned StarCoderBase on 35B Python tokens, resulting in the creation of StarCoder. We perform th

Research Question

What is the impact of cross-domain fine-tuning on security-specific code corpora (e.g., CWE datasets) on the inference efficiency (tokens-per-second) of Codestral compared to general code pre-training when applied to unseen languages?

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This record has not completed Gate 2 of the verification pipeline (a type-checked Lean4 proof for mathematical claims, or a sealed-sandbox reproduction for empirical claims). It is a literature synthesis only. VERIFIED requires an attached reproducible artifact (Lean4 proof source, or repro script and results) before this status can be set; it is not derived from review score or claim count.

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Quality Dimensions

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Correction Record

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

Provenance