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New HERMES framework enhances LLM performance in software engineering tasks

By PulseAugur Editorial · [3 sources] ·

Researchers have developed HERMES, a Harness Engineering framework designed to improve the performance of large language models (LLMs) on complex software engineering tasks. HERMES utilizes modular, executable "Dev-Primitives" that transform repository components into active agents capable of natural-language reasoning and self-modification. Experiments show HERMES outperforms baseline harnesses by an average of 12.4%, and even with a smaller Qwen3-8B model, it achieves performance close to a GPT-5.6 Sol configuration while reducing inference costs. AI

IMPACT This framework could significantly improve the reliability and efficiency of LLM-driven software development, potentially reducing costs and accelerating workflows.

RANK_REASON The cluster contains a research paper detailing a new framework and methodology for software engineering with LLMs.

Read on Hugging Face Daily Papers →

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New HERMES framework enhances LLM performance in software engineering tasks

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COVERAGE [3]

  1. arXiv cs.AI TIER_1 English(EN) · Haibo Jin, Xinjie Li, Peng Kuang, Haohan Wang ·

    Harness Engineering for Software Engineering via Modular Executable Dev-Primitives

    arXiv:2610.07832v1 Announce Type: cross Abstract: Large language models (LLMs) equipped with terminal access have demonstrated strong capabilities in automating software engineering tasks. However, existing agents remain brittle on long-horizon workflows, where they must repeated…

  2. arXiv cs.MA (Multiagent) TIER_1 English(EN) · Haohan Wang ·

    Harness Engineering for Software Engineering via Modular Executable Dev-Primitives

    Large language models (LLMs) equipped with terminal access have demonstrated strong capabilities in automating software engineering tasks. However, existing agents remain brittle on long-horizon workflows, where they must repeatedly reconstruct program state scattered across sour…

  3. Hugging Face Daily Papers TIER_1 English(EN) ·

    Harness Engineering for Software Engineering via Modular Executable Dev-Primitives

    Large language models (LLMs) equipped with terminal access have demonstrated strong capabilities in automating software engineering tasks. However, existing agents remain brittle on long-horizon workflows, where they must repeatedly reconstruct program state scattered across sour…

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