3️⃣LLMs that are better at next-token prediction have higher, earlier ID peaks.

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2️⃣ The ID peak (beige) is where different LLMs are most similar (big shapes).

All LLMs share this high-dimensional phase of linguistic abstraction, but...

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... the ID peak marks where syntactic, semantic, and abstract linguistic features like toxicity and sentiment are first decodable.

⭐use these layers for downstream transfer!

(e.g., for brain encoding models, see arxiv.org/abs/2409.05771)

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1️⃣ The ID peak is linguistically relevant.

- it collapses on shuffled text (destroying syntactic/semantic structure)
- it grows over the course of training...

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Here's our work accepted to #ICLR2025!

We look at how intrinsic dimension evolves over LLM layers, spotting a universal high-dimensional phase.

This ID peak is where:

- linguistic features are built
- different LLMs are most similar,

with implications for task transfer

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