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    Announcement

    Sherpa is introduced as a framework for training language models to teach adaptively

    The Sherpa announcement argues that good teaching adjusts to learners’ preferences, rather than simply solving problems.

    Diyi YangDY
    Weixian XuWX
    Yanzhe ZhangYZ
    6 Sources, ,

    TLDR

    A post introducing Sherpa describes it as a framework for training language models to teach adaptively. It argues that being good at math problems is different from being a good teacher: AI should adjust to each learner’s preferences and help people grow, not replace them.

    Combined views

    3.8K

    6 Sources, first seen 2h ago

    Combined views

    3.8K

    6 Sources, first seen 2h ago

    51 likes
    2h ago
    first seen 2h ago
    51 likes
    1 comments
    15 saves
    33 reposts
    Featured Source
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    33 reposts

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    6 Sources

    Weixian Xu@WeixianXuLanguage models already excel at math, but human growth remains essential: we need AI to teach people, not replace them! Teaching is different from solving. As the Chinese principle “因材施教” suggests, preferences differ from person to person, and a good teacher should adapt their teaching to each learner. We introduce Sherpa, a framework for training LLMs to teach adaptively.2h
    Diyi Yang@Diyi_YangRT @WeixianXu: Language models already excel at math, but human growth remains essential: we need AI to teach people, not replace them! Te…2h
    Yanzhe Zhang@StevenyzZhangAt the end of the day, it is all about human learning and understanding. In this work, we explored how to improve the personalized learning experience by training LLM teachers to teach adaptively.2h
    Zora Wang@ZhiruoWIncreasing AI capabilities doesn’t have to come at the expense of humans. We can harness powerful AI to educate and empower people‼️ We introduce Sherpa, a framework for training LLMs to teach simulated students adaptively, with promising transfer to human learners.1h

    6 Sources

    Weixian Xu@WeixianXuLanguage models already excel at math, but human growth remains essential: we need AI to teach people, not replace them! Teaching is different from solving. As the Chinese principle “因材施教” suggests, preferences differ from person to person, and a good teacher should adapt their teaching to each learner. We introduce Sherpa, a framework for training LLMs to teach adaptively.2h
    Diyi Yang@Diyi_YangRT @WeixianXu: Language models already excel at math, but human growth remains essential: we need AI to teach people, not replace them! Te…2h
    Yanzhe Zhang@StevenyzZhangAt the end of the day, it is all about human learning and understanding. In this work, we explored how to improve the personalized learning experience by training LLM teachers to teach adaptively.2h
    Zora Wang@ZhiruoWIncreasing AI capabilities doesn’t have to come at the expense of humans. We can harness powerful AI to educate and empower people‼️ We introduce Sherpa, a framework for training LLMs to teach simulated students adaptively, with promising transfer to human learners.1h