cross-layer-transcoder

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LLM-Interp / CLT-Forge

A Mechanistic Interpretability Toolkit for Cross-Layer Transcoder Training and Attribution-Graph Visualization

transcoder visual-interface mechanistic-interpretability ai-interpretability attribution-graphs auto-interpretability cross-layer-transcoder transformer-circuits

Updated Jul 30, 2026
Python

peppinob-ol / attribution-graph-probing

Star

Automates attribution-graph analysis via probe prompting: circuit-trace a prompt, auto-generate concept probes, profile feature activations, cluster supernodes.

graph-analysis sparse-autoencoders mechanistic-interpretability llm-interpretability research-tooling circuit-tracing attribution-graphs probe-prompting prompt-probing neuronpedia feature-activation supernodes cross-layer-transcoder

Updated Jun 5, 2026
Jupyter Notebook

KOKOSde / sparse-clt

Star

Cross-Layer Transcoder (CLT) library for extracting sparse interpretable features from transformer models. Batched processing, memory-efficient, works with any LLM/VLM.

transformers pytorch feature-extraction interpretability pypi-package llm mechanistic-interpretability vision-language-models cross-layer-transcoder

Updated Mar 23, 2026
Python

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