Neuron Dependency Graphs: A Causal Abstraction of Neural Networks
Authors: Yaojie Hu, Jin Tian
ICML 2022 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | We empirically show that an NDG is a causal abstraction of the corresponding neural network that unfolds the same way under causal interventions using the theory by Geiger et al. (2021a). Code is available at https://github.com/phimachine/ndg. ... Experimental results empirically support the alignment condition. ... We extract neuron dependency graphs on a diverse set of datasets and architectures to demonstrate the generality of our method. Table 1 lists the datasets and architectures |
| Researcher Affiliation | Academia | Yaojie Hu 1 Jin Tian 1 ... 1Department of Computer Science, Iowa State University, United States. Correspondence to: Yaojie Hu <jhu@iastate.edu>. |
| Pseudocode | Yes | Algorithm 1 Interchange intervention with a NDG |
| Open Source Code | Yes | Code is available at https://github.com/phimachine/ndg. |
| Open Datasets | Yes | We extract neuron dependency graphs on a diverse set of datasets and architectures to demonstrate the generality of our method. Table 1 lists the datasets and architectures (Le Cun et al., 1998; Socher et al., 2013; Conneau et al., 2017; Reimers & Gurevych, 2019; Welinder et al., 2010; Lu et al., 2021; Sanh et al., 2019; Dosovitskiy et al., 2021; He et al., 2021; Zhou et al., 2019; Feng et al., 2020; Liu et al., 2019; Devlin et al., 2018). |
| Dataset Splits | Yes | For the datasets with only the training set and the test set, we leave 10% of the training set for validation. |
| Hardware Specification | No | The paper does not provide specific hardware details such as GPU or CPU models, or cloud instance types used for experiments. |
| Software Dependencies | No | The Py Torch program using Huggingface library (Wolf et al., 2019) to select layers is in Figure 4. |
| Experiment Setup | Yes | Threshold parameter α is used in Eq. (1) to extract the neuron dependency graphs. ... Threshold α is manually selected to improve interchange intervention accuracy. ... For Re LU, we select Tϕ = 1, Fϕ = 0. For sigmoid, Tϕ = , Fϕ = . |