一个用于ARC-AGI-2视觉推理基准测试的新求解器，在公开评估集上取得了76.1%的最高分。该求解器将文本、图像和代码等推理模态视为搜索算子，生成多样化的候选解决方案。然后，它采用整体判断方法，在单个提示中同时比较所有候选追踪，这有助于恢复正确的少数派假设。该求解器显著优于GPT-5.2 Pro和Gemini 3 Pro等领先模型。 AI
影响 在ARC-AGI-2基准测试上创下新的最先进水平，展示了超越现有前沿模型的推理能力提升。
排序理由 该集群是关于一篇详细介绍特定AI基准测试新求解器的新研究论文。[lever_c_demoted from research: ic=1 ai=1.0]
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arXiv:2606.31543v1 Announce Type: new Abstract: Large language models can produce fluent, internally coherent reasoning traces for abstract reasoning tasks while still being confidently wrong - making selection among candidates, not just generation, the central challenge. I prese…
Large language models can produce fluent, internally coherent reasoning traces for abstract reasoning tasks while still being confidently wrong - making selection among candidates, not just generation, the central challenge. I present a solver for ARC-AGI-2, a few-shot visual rea…