Papers by Temurbek Rahmatullaev

1 papers
LLM-Microscope: Uncovering the Hidden Role of Punctuation in Context Memory of Transformers (2025.findings-naacl)

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Challenge: Large Language Models (LLMs) encode and store contextual information, but internal mechanisms are opaque.
Approach: They propose a toolkit that assesses token-level nonlinearity, evaluates contextual memory, visualizes intermediate layer contributions and measures intrinsic dimensionality of representations.
Outcome: The proposed framework assesses token-level nonlinearity, evaluates contextual memory, visualizes intermediate layer contributions, and measures the intrinsic dimensionality of representations.

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