# Mechanistic Interpretability: Research Digest

> 10 foundational papers with 3,902 combined citations, plus the latest arXiv preprints.

- **Canonical:** https://agentflare.org/scholar/mechanistic-interpretability-research-digest.html
- **Updated:** 2026-10-18
- **Category:** scholar
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## Key data

- **Field:** mechanistic interpretability neural networks
- **Foundational:** 10
- **Recent (arXiv):** 8
- **Updated:** 2026-10-18

10 foundational papers with 3,902 combined citations, plus the latest arXiv preprints.

_…full analysis and the complete dataset are available to agents for $0.02 — fetch `/scholar/mechanistic-interpretability-research-digest.data.json` (HTTP 402)._

## Sources

1. [Mechanistic interpretability for AI safety--a review](https://arxiv.org/abs/2404.14082)
2. [Towards automated circuit discovery for mechanistic interpretability](https://proceedings.neurips.cc/paper_files/paper/2023/hash/34e1dbe95d34d7ebaf99b9bcaeb5b2be-Abstract-Conference.html)
3. [Open problems in mechanistic interpretability](https://arxiv.org/abs/2501.16496)
4. [Bridging the black box: a survey on mechanistic interpretability in AI](https://dl.acm.org/doi/abs/10.1145/3787104)
5. [Exploring mechanistic interpretability in large language models: Challenges, approaches, and insights](https://ieeexplore.ieee.org/abstract/document/11011640/)
6. [Progress measures for grokking via mechanistic interpretability](https://arxiv.org/abs/2301.05217)
7. [Everything, everywhere, all at once: Is mechanistic interpretability identifiable?](https://proceedings.iclr.cc/paper_files/paper/2025/hash/51157713f1f1f572a05647e1aef1b1ed-Abstract-Conference.html)
8. [A mathematical philosophy of explanations in mechanistic interpretability](https://ojs.aaai.org/index.php/AIES/article/view/36547)
9. [Causal abstraction: A theoretical foundation for mechanistic interpretability](http://www.jmlr.org/papers/v26/23-0058.html)
10. [A practical review of mechanistic interpretability for transformer-based language models](https://arxiv.org/abs/2407.02646)
11. [Spurious Attention Heads in Vision Transformers: Mechanistic Identification of Annotation-Driven Bias in Medical Chest X-Ray Analysis](https://arxiv.org/abs/2610.21638v1)
12. [Learning and Forecasting Multiscale Spatiotemporal Epidemic Dynamics with Lagrangian-Eulerian Graph Neural ODEs](https://arxiv.org/abs/2610.21223v1)
13. [Complete or Sparse: A Tale of Two Identifiabilities](https://arxiv.org/abs/2610.20851v1)
14. [Interpreting Language Model Parameters](https://arxiv.org/abs/2610.20748v1)
15. [Sparse Autoencoders for Mechanistic Interpretability in NLP: A Critical Survey of Recoverability, Interpretability, and Utility](https://arxiv.org/abs/2610.20139v1)
16. [Sparse Transformer: a Controlled Testbed for Mechanistic Interpretability](https://arxiv.org/abs/2610.19907v1)
17. [Monitoring latent reasoning in looped language models](https://arxiv.org/abs/2610.18127v1)
18. [Neural networks are more modular than single neurons suggest](https://arxiv.org/abs/2610.12842v2)

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