From Atoms to Trees: Building a Structured Feature Forest with Hierarchical Sparse Autoencoders | ScienceToStartup | ScienceToStartup

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References (24)

[1]

Attribution-Guided Distillation of Matryoshka Sparse Autoencoders

2025Cristina P. Martin-Linares, Jonathan P. Ling

[2]

OrtSAE: Orthogonal Sparse Autoencoders Uncover Atomic Features

2025Anton Korznikov, Andrey V. Galichin et al.

[3]

Feature Hedging: Correlated Features Break Narrow Sparse Autoencoders

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"Introducing HSAE, a scalable tool for building and analyzing hierarchical conceptual structures in LLMs using sparse autoencoders."

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From Atoms to Trees: Building a Structured Feature Forest with Hierarchical Sparse Autoencoders

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References (24)

Founder's Pitch

"Introducing HSAE, a scalable tool for building and analyzing hierarchical conceptual structures in LLMs using sparse autoencoders."

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From Atoms to Trees: Building a Structured Feature Forest with Hierarchical Sparse Autoencoders

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References (24)

Founder's Pitch

"Introducing HSAE, a scalable tool for building and analyzing hierarchical conceptual structures in LLMs using sparse autoencoders."

Commercial Viability Breakdown

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