English

diagNNose: A Library for Neural Activation Analysis

Computation and Language 2020-11-16 v1 Machine Learning

Abstract

In this paper we introduce diagNNose, an open source library for analysing the activations of deep neural networks. diagNNose contains a wide array of interpretability techniques that provide fundamental insights into the inner workings of neural networks. We demonstrate the functionality of diagNNose with a case study on subject-verb agreement within language models. diagNNose is available at https://github.com/i-machine-think/diagnnose.

Keywords

Cite

@article{arxiv.2011.06819,
  title  = {diagNNose: A Library for Neural Activation Analysis},
  author = {Jaap Jumelet},
  journal= {arXiv preprint arXiv:2011.06819},
  year   = {2020}
}

Comments

Accepted to the Third BlackboxNLP Workshop on Analyzing and Interpreting Neural Networks for NLP, EMNLP 2020

R2 v1 2026-06-23T20:10:17.947Z