Transformers converge to invariant algorithmic cores | ScienceToStartup | ScienceToStartup

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References (44)

[1]

Everything, Everywhere, All at Once: Is Mechanistic Interpretability Identifiable?

2025Maxime M'eloux, Silviu Maniu et al.

[2]

Archetypal SAE: Adaptive and Stable Dictionary Learning for Concept Extraction in Large Vision Models

2025Thomas Fel, E. Lubana et al.

[3]

Open Problems in Mechanistic Interpretability

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"This research identifies invariant algorithmic cores in transformers but lacks direct productization potential."

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Transformers converge to invariant algorithmic cores

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"This research identifies invariant algorithmic cores in transformers but lacks direct productization potential."

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Transformers converge to invariant algorithmic cores

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References (44)

Founder's Pitch

"This research identifies invariant algorithmic cores in transformers but lacks direct productization potential."

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