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Software engineering principles enhance coding LLMs, paper shows

A new paper explores how software engineering principles can be applied to enhance the development and capabilities of large language models (LLMs) designed for coding tasks. Researchers developed a pipeline called RefactorForge, which uses refactoring knowledge and established SE tools to create training data. Fine-tuning a 92B-parameter coding LLM with this data led to significant improvements on benchmarks like RefactorBench and SWE-Bench ProMax, as well as in real-world issue resolution. AI

IMPACT Applying software engineering principles to LLM development could lead to more capable and reliable coding assistants for developers.

RANK_REASON The cluster contains an academic paper detailing research into improving LLMs for software engineering tasks. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.LG →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

Software engineering principles enhance coding LLMs, paper shows

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The cluster contains an academic paper detailing research into improving LLMs for software engineering tasks. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.LG TIER_1 English(EN) · Amir M. Ebrahimi, Mohammed Mehedi Hasan, Seyed Shayan Daneshvar, Jiahuei Lin, Gopi Krishnan Rajbahadur, Ahmed E. Hassan ·

    Software Engineering LLMs: Why We Need Them and How Software Engineering Helps Build Them

    arXiv:2610.33851v1 Announce Type: cross Abstract: Software engineering (SE) expertise can shape how coding large language models (LLMs) are trained and which engineering capabilities they acquire. We examine this role through an industrial case study of capability-focused trainin…