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English(EN) Can LLMs Build a MaxSAT Solver from Papers? The CoreForge Experience

LLM 用于从研究论文构建 MaxSAT 求解器

研究人员探索了使用大型语言模型 (LLM) 构建 MaxSAT 求解器(命名为 CoreForge)的可能性,该求解器通过解读研究论文而非依赖现有代码库来完成。迭代过程包括与 ChatGPT 的讨论、通过 Codex 提示生成代码以及 LLM 辅助的代码审计。尽管 LLM 辅助的方法在实现求解器组件和通过评估方面显示出潜力,但生成的求解器的性能未能与手动设计的求解器相匹配,这凸显了人类监督和外部验证的必要性。 AI

影响 展示了 LLM 从研究中进行复杂代码生成的强大能力,但性能仍需人类监督。

排序理由 该集群包含一篇详细介绍研究项目及其发现的学术论文。

在 arXiv cs.AI 阅读 →

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LLM 用于从研究论文构建 MaxSAT 求解器

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报道来源 [2]

  1. arXiv cs.AI TIER_1 English(EN) · Ruben Martins ·

    大型语言模型能否从论文中构建MaxSAT求解器?CoreForge的经验

    arXiv:2607.14818v1 Announce Type: cross Abstract: We report on CoreForge, an experience in using large language models (LLMs) to build an unweighted MaxSAT solver from research papers rather than from an existing solver codebase. The project focuses on unsatisfiability-based MaxS…

  2. arXiv cs.AI TIER_1 English(EN) · Ruben Martins ·

    大型语言模型能否从论文中构建MaxSAT求解器?CoreForge的经验

    We report on CoreForge, an experience in using large language models (LLMs) to build an unweighted MaxSAT solver from research papers rather than from an existing solver codebase. The project focuses on unsatisfiability-based MaxSAT algorithms and follows an iterative workflow th…