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arXiv — cs.AI

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标题为英语Verifiable Efficiency Limits of Innate LLM Planning in Sliding Puzzles

arXiv:2610.36415v1 Announce Type: new Abstract: Tool-assisted planning success can reflect external search and verification, leaving a model's unaided planning ability unresolved. We isolate innate planning through complete plans generated in one response without tools or…

arXiv — cs.AI作者: Yezhou Cheng, Charles Ling2026年10月28日 (13小时前)
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  • arXiv:2610.36415v1 Announce Type: new Abstract: Tool-assisted planning success can reflect external search and verification, leaving a model's unaided planning ability unresolved
  • We isolate innate planning through complete plans generated in one response without tools or…
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Verifiable Efficiency Limits of Innate LLM Planning in Sliding Puzzles

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