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diagNNose: A Library for Neural Activation Analysis

arXiv 2011.06819 ↗First posted 13 Nov 2020cs.CL cs.LGcited by 7

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Abstract (arXiv)

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.

Key facts. Cited by 7 papers in the map (data through 7 Oct 2026). First posted on arXiv 13 Nov 2020.

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Citing papers per year: 2021: 4; 2022: 1; 2023: 1; 2024: 1.

7 papers.