Tag

#model interpretability

3 articles

Nous Research Releases Contrastive Neuron Attribution (CNA): Sparse MLP Circuit Steering Without SAE Training or Weight Modification

Nous Research introduces Contrastive Neuron Attribution (CNA), a method to steer LLM behavior without training or weight modification, preserving general capabilities.

May 236

A Coding Guide Implementing SHAP Explainability Workflows with Explainer Comparisons, Maskers, Interactions, Drift, and Black-Box Models

A new tutorial from MarkTechPost provides a comprehensive guide to implementing SHAP explainability workflows, comparing various explainers and exploring advanced techniques like interactions and model drift detection.

May 179

How to Build an Explainable AI Analysis Pipeline Using SHAP-IQ to Understand Feature Importance, Interaction Effects, and Model Decision Breakdown

A new tutorial demonstrates how to build an explainable AI pipeline using SHAP-IQ to uncover feature importance and interaction effects in machine learning models.

Mar 178