Zach does mechanistic interpretability

• I’m working on independent mech interp research these days!
• My interest is in sparse representations, structured dependence, and interp methods useful for both biology and LLM tasks.

I’ll be presenting at ICML 2026! I’ll be talking about my work building dependence structure off of SAEs, spotlight in the mechanistic interpretability workshop.

Contact Me

hey@zachmaas.com ⋅ @zmaas

Highlighted Work:

• Conditional Dependence Structure in Sparse Autoencoder Features: ICML Mech Interp Workshop 2026 spotlight. Dependence graph structure in SAEs
• Graph Structure Compresses Contrastive Neuron Steering Targets: Can we steer LLM behavior using only MLPs + structured dependence?
• Preliminary Results on Graph SAEs: Building dependence graphs off of SAEs to understand their structure
• Research Notes: Sequence to Read Models: Notes on how to build (and not build) sequence-to-read genomic models

Papers I Liked Recently:

• Subliminal Learning Is Steering Vector Distillation
• Language Model Circuits Are Sparse in the Neuron Basis
• Do Sparse Autoencoders Capture Concept Manifolds?
• Targeted Neuron Modulation via Contrastive Pair Search