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    LLMs appear to learn novel tasks more reliably from rules than examples

    The authors say their EMNLP 2026 paper compares in-context learning from rules and examples across diverse tasks and models.

    Najoung Kim 🫠NK
    Xiang FuXF
    3 Sources, ,

    TLDR

    The authors of an EMNLP 2026 paper say they compared how LLMs learn novel tasks in context from rules versus examples across diverse tasks and models. They report that LLMs generally learned more reliably from rules.

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    3 Sources, first seen 7h ago

    Combined views

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    3 Sources, first seen 7h ago

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    first seen 7h ago
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    3 Sources

    Xiang Fu@xiangfu1/ Do LLMs learn novel tasks better in-context from rules or from examples? In our #EMNLP2026 Main paper, we systematically compare their learning efficacy across diverse tasks and models. We find that LLMs generally learn more reliably from rules than from examples.7h
    Najoung Kim 🫠@najoungkimRT @xiangfu: 1/ Do LLMs learn novel tasks better in-context from rules or from examples? In our #EMNLP2026 Main paper, we systematically c…3h

    3 Sources

    Xiang Fu@xiangfu1/ Do LLMs learn novel tasks better in-context from rules or from examples? In our #EMNLP2026 Main paper, we systematically compare their learning efficacy across diverse tasks and models. We find that LLMs generally learn more reliably from rules than from examples.7h
    Najoung Kim 🫠@najoungkimRT @xiangfu: 1/ Do LLMs learn novel tasks better in-context from rules or from examples? In our #EMNLP2026 Main paper, we systematically c…3h