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English(EN) Which LLM is Best for Translating Natural Language Goals to PDDL

大型语言模型在将自然语言转换为PDDL方面表现出高准确性，Gemini 2.5 Flash领先

作者 PulseAugur 编辑部 · [1 个来源] ·

一篇新论文评估了大型语言模型（LLM）在将自然语言测试目标转换为PDDL（规划领域定义语言）以进行自动化规划方面的有效性。研究发现，当前的大型语言模型表现出很高的正确性，其中Gemini 2.5 Flash的准确率达到96%，而GPT-4.1在响应速度方面领先。尽管取得了重大进展，但由于语言歧义和领域表示的局限性，挑战依然存在。 AI

影响 增强了大型语言模型在自动化规划系统中弥合人类意图与机器执行之间差距的潜力。

排序理由 该集群包含一篇评估大型语言模型在特定任务上性能的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.AI 阅读 →

AI 生成摘要 · Google Gemini · 来自 1 个来源。 我们如何撰写摘要 →

大型语言模型在将自然语言转换为PDDL方面表现出高准确性，Gemini 2.5 Flash领先

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该集群包含一篇评估大型语言模型在特定任务上性能的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

  1. arXiv cs.AI TIER_1 English(EN) · Tomas Balyo, Lukas Chrpa, G. Michael Youngblood ·

    哪种大型语言模型最适合将自然语言目标翻译成PDDL

    arXiv:2609.18731v1 Announce Type: new Abstract: Bridging the gap between human intent and machine execution remains a challenge in automated planning, where expressing goals in formal languages like PDDL restricts accessibility to non-experts. This paper empirically evaluates whe…

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