Notice: The reproducibility variables underlying each score are classified using an automated LLM-based pipeline, validated against a manually labeled dataset. LLM-based classification introduces uncertainty and potential bias; scores should be interpreted as estimates. Full accuracy metrics and methodology are described in Coakley et alK. L. Coakley, T. Snelleman, H. Hoos, and O. E. Gundersen, "The embrace of open science: An analysis of a decade of AI research and 56 800 conference papers," Under Review, 2026..
Causal Abstractions of Neural Networks
Authors: Atticus Geiger, Hanson Lu, Thomas Icard, Christopher Potts
NeurIPS 2021 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | We apply this method in a case study to analyze neural models trained on Multiply Quantified Natural Language Inference (MQNLI) corpus, a highly complex NLI dataset that was constructed with a tree-structured natural logic causal model. |
| Researcher Affiliation | Academia | Atticus Geiger , Hanson Lu , Thomas Icard, and Christopher Potts Stanford Stanford, CA 94305-2150 EMAIL |
| Pseudocode | No | The paper does not contain any pseudocode or algorithm blocks. |
| Open Source Code | Yes | We provide tools for causal abstraction analysis at http://github.com/hansonhl/antra and the code base for this paper at http://github.com/atticusg/Interchange |
| Open Datasets | Yes | The Multiply Quantified NLI (MQNLI) dataset of Geiger et al. [10] contains templatically generated English-language NLI examples... |
| Dataset Splits | Yes | MQNLI has train/dev/test splits that vary in their difficulty. |
| Hardware Specification | No | The paper does not provide specific hardware details (e.g., GPU/CPU models, memory) used for running experiments. |
| Software Dependencies | No | The paper mentions BERT and Huggingface's transformers but does not provide specific version numbers for these or other software dependencies. |
| Experiment Setup | No | Additional model and training details are given in Appendix B. (This indicates details exist but are not in the provided main text). |