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arXiv — cs.AI

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标题为英语Learning Symbolic Constraint Representations from Examples: A Neuro-Symbolic Approach

arXiv:2609.12267v1 Announce Type: new Abstract: Learning user-defined concepts as constraint networks has been extensively studied in the constraint acquisition (CA) literature. However, existing approaches typically rely on intensive interactions with a human oracle, making the…

arXiv — cs.AI作者: Nassim Belmecheri, Arnaud Gotlieb, Nadjib Lazaar, Helge Spieker2026年9月14日 (9月14日)
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  • arXiv:2609.12267v1 Announce Type: new Abstract: Learning user-defined concepts as constraint networks has been extensively studied in the constraint acquisition (CA) literature
  • However, existing approaches typically rely on intensive interactions with a human oracle, making the…
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Learning Symbolic Constraint Representations from Examples: A Neuro-Symbolic Approach

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