ai-research-04-mechanistic-interpretability-pyvene
Guides users in performing causal interventions on PyTorch models using pyvene's framework for reproducible experiments.
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The ai-research-04-mechanistic-interpretability-pyvene skill was audited on Jun 8, 2026 and we found 10 security issues across 1 threat category. Review the findings below before installing.
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Security Issues
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| 14 | **Paper**: [pyvene: A Library for Understanding and Improving PyTorch Models via Interventions](https://aclanthology.org/2024.naacl-demo.16) (NAACL 2024) |
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| 449 | - [pyvene 101](https://stanfordnlp.github.io/pyvene/tutorials/pyvene_101.html) |
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| 450 | - [Causal Tracing Tutorial](https://stanfordnlp.github.io/pyvene/tutorials/advanced_tutorials/Causal_Tracing.html) |
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| 451 | - [IOI Circuit Replication](https://stanfordnlp.github.io/pyvene/tutorials/advanced_tutorials/IOI_Replication.html) |
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| 452 | - [DAS Introduction](https://stanfordnlp.github.io/pyvene/tutorials/advanced_tutorials/DAS_Main_Introduction.html) |
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| 455 | - [Locating and Editing Factual Associations in GPT](https://arxiv.org/abs/2202.05262) - Meng et al. (2022) |
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| 456 | - [Inference-Time Intervention](https://arxiv.org/abs/2306.03341) - Li et al. (2023) |
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| 457 | - [Interpretability in the Wild](https://arxiv.org/abs/2211.00593) - Wang et al. (2022) |
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| 460 | - [Official Docs](https://stanfordnlp.github.io/pyvene/) |
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| 461 | - [API Reference](https://stanfordnlp.github.io/pyvene/api/) |
Scanned on Jun 8, 2026
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