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    How training data from many sources may shape LLM internals

    A post sharing new work from Simplex says the belief geometry over data from many sources forms “telescoping cones,” and that transformers represent those structures.

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    TLDR

    LLM training data comes from many sources. An author sharing new work from Simplex says the belief geometry over that data forms “telescoping cones,” which transformers represent in their internal activations. The author also announced that the write-up had been published on LessWrong for discussion, calling it especially important for people interested in understanding LLM internals.

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    1 Source, first seen 20d ago

    Combined views

    3.4K

    1 Source, first seen 20d ago

    68 likes
    20d ago
    first seen 20d ago
    68 likes
    1 comments
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    8 reposts

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    1 comments
    39 saves
    8 reposts

    Sentiment

    Positive——Negative

    Summary

    Not enough discussion yet.

    No sentiment analysis available yet.

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    1 Source

    @adamimosWe've just published our nonergodic post on @lesswrong . Especially good for conversation/discussion! We think this is especially important for those interested in understanding model internals in LLMs. https://www.lesswrong.com/posts/JfJ4WTRHmooPBWRFv/the-geometry-of-nonergodic-composition

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    @adamimosWe've just published our nonergodic post on @lesswrong . Especially good for conversation/discussion! We think this is especially important for those interested in understanding model internals in LLMs. https://www.lesswrong.com/posts/JfJ4WTRHmooPBWRFv/the-geometry-of-nonergodic-composition