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New method makes Transformer LLM hidden axes measurable and controllable

By PulseAugur Editorial · [4 sources] ·

Researchers have developed a "Canonical Basis for Language Models" (CBLL), a method that transforms the coordinate system of Transformer LLMs to make each hidden axis independently measurable and controllable. This technique, detailed in a Zenodo paper and accompanied by a GitHub repository, allows for the analysis of model behavior, such as identifying specific functional axes and their impact on performance metrics like perplexity and MMLU. The CBLL has been demonstrated to be lossless and architecturally general, showing consistent results across different normalization types and models like Qwen 2.5 0.5B and SmolLM2 1.7B. AI

IMPACT Enables deeper understanding and potential manipulation of LLM internal workings, facilitating more targeted research and development.

RANK_REASON The cluster describes a new research paper and accompanying code that introduces a novel method for analyzing and controlling internal components of Transformer LLMs.

Read on r/singularity →

AI-generated summary · Google Gemini · from 4 sources. How we write summaries →

New method makes Transformer LLM hidden axes measurable and controllable

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The cluster describes a new research paper and accompanying code that introduces a novel method for analyzing and controlling internal components of Transformer LLMs.
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COVERAGE [4]

  1. Lobsters — AI tag TIER_1 English(EN) · github.com via Yogthos ·

    Canonical-basis realignment for Transformer LLMs: every hidden axis becomes independently measurable and controllable

    <p>The code essentially gives you a way to rotate a Transformer's internal coordinate system into a canonical basis that aligns with its own weight matrices in a lossless way. By absorbing the normalization gains directly into the adjacent weights and using orthogonal matrices bu…

  2. Mastodon — mastodon.social TIER_1 English(EN) · lobsters ·

    Canonical-basis realignment for Transformer LLMs: every hidden axis becomes independently measurable and controllable https:// lobste.rs/s/wg65qn # ai https://

    Canonical-basis realignment for Transformer LLMs: every hidden axis becomes independently measurable and controllable https:// lobste.rs/s/wg65qn # ai https:// github.com/todotge/canonical-b asis

    LINKS lobste.rs/…/wg65qn github.com/…/canonical-basis
  3. Mastodon — mastodon.social TIER_1 English(EN) · [email protected] ·

    Canonical-basis realignment for Transformer LLMs: every hidden axis becomes independently measurable and controllable https://github.com/todotge/canonical-basis

    Canonical-basis realignment for Transformer LLMs: every hidden axis becomes independently measurable and controllable https://github.com/todotge/canonical-basis # AI # MachineLearning # LLM

    LINKS github.com/…/canonical-basis
  4. r/singularity TIER_2 English(EN) · /u/yogthos ·

    Canonical-basis realignment for Transformer LLMs: every hidden axis becomes independently measurable and controllable.

    <table> <tr><td> <a href="https://www.reddit.com/r/singularity/comments/1w1wt5y/canonicalbasis_realignment_for_transformer_llms/"> <img alt="Canonical-basis realignment for Transformer LLMs: every hidden axis becomes independently measurable and controllable." src="https://extern…

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