HiPACE: Hierarchical Phase-Boundary Analysis and Controlled Evaluation of Feature Absorption in Sparse Autoencoders
cs.AI
Submitted: 2026-08-26
Updated: 2026-08-26
Terminology
Sources
- Pythia: A Suite for Analyzing Large Language Models Across Training and Scaling
- A is for Absorption: Studying Feature Splitting and Absorption in Sparse Autoencoders
- Feature Hedging: Correlated Features Break Narrow Sparse Autoencoders
- Message Passing Algorithms for Compressed Sensing
- Toy Models of Superposition
- Archetypal SAE: Adaptive and Stable Dictionary Learning for Concept Extraction in Large Vision Models
- Scaling and evaluating sparse autoencoders
- Sparse Autoencoders Do Not Find Canonical Units of Analysis
- Gemma Scope: Open Sparse Autoencoders Everywhere All At Once on Gemma 2
- k-Sparse Autoencoders
- Jumping Ahead: Improving Reconstruction Fidelity with JumpReLU Sparse Autoencoders
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