--- title: "Who cites The Hydra Effect: Emergent — 46 citing papers" description: "46 papers of the Elamur Research library cite «The Hydra Effect: Emergent Self-repair in Language Model Computations», found in their…" canonical: "https://research.elamur.ai/free/en/papers/mcgrath-2023-hydra-effect-emergent-self-repair/cited-by/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/mcgrath-2023-hydra-effect-emergent-self-repair/cited-by/) [home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [The Hydra Effect: Emergent Self-repair in…](https://md.research.elamur.ai/free/en/papers/mcgrath-2023-hydra-effect-emergent-self-repair/) / cited by # Who cites «The Hydra Effect: Emergent Self-repair in Language Model Computations» 46 papers of our library cite it (of the 149,439 whose bibliographies we read) · 16 with a page here, the most cited first · [← back to «The Hydra Effect: Emergent Self-repair in Language Model Computations»](https://md.research.elamur.ai/free/en/papers/mcgrath-2023-hydra-effect-emergent-self-repair/) 1. **[Explainability for Large Language Models: A Survey](https://md.research.elamur.ai/free/en/papers/zhao-2023-explainability-large-language-models-survey/) [ACM Transactions on Intelligent Systems and Technology](https://md.research.elamur.ai/free/en/venues/acm-transactions-on-intelligent-systems-and-technology/)**Haiyan Zhao, Hanjie Chen, Fan Yang, et al.*2023 · 790 citations* 2. [**Representation Engineering: A Top-Down Approach to AI Transparency arXiv:2310.01405**Andy Zou, Long Phan, Sarah Chen, et al.*2023 · 397 citations*](https://md.research.elamur.ai/free/en/papers/zou-2023-representation-engineering-top-down-approach/) 3. [**AI Alignment: A Comprehensive Survey arXiv:2310.19852**Jiaming Ji, Tianyi Qiu, Boyuan Chen, et al.*2023 · 173 citations*](https://md.research.elamur.ai/free/en/papers/ji-2023-ai-alignment-comprehensive-survey/) 4. [**Emergent Linear Representations in World Models of Self-Supervised Sequence Models arXiv:2309.00941**Neel Nanda, Andrew Lee, Martin Wattenberg*2023 · 116 citations*](https://md.research.elamur.ai/free/en/papers/nanda-2023-emergent-linear-representations-world-models/) 5. [**Mechanistic Interpretability for AI Safety — A Review arXiv:2404.14082**Leonard Bereska, Efstratios Gavves*2024 · 108 citations*](https://md.research.elamur.ai/free/en/papers/bereska-2024-mechanistic-interpretability-ai-safety-review/) 6. [**Towards Best Practices of Activation Patching in Language Models: Metrics and Methods arXiv:2309.16042**Fred Zhang, Neel Nanda*2023 · 97 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2023-towards-best-practices-activation-patching/) 7. [**Foundational Challenges in Assuring Alignment and Safety of Large Language Models arXiv:2404.09932**Usman Anwar, Abulhair Saparov, Javier Rando, et al.*2024 · 87 citations*](https://md.research.elamur.ai/free/en/papers/anwar-2024-foundational-challenges-assuring-alignment-safety/) 8. [**A Primer on the Inner Workings of Transformer-based Language Models arXiv:2405.00208**Javier Ferrando, Gabriele Sarti, Arianna Bisazza, et al.*2024 · 72 citations*](https://md.research.elamur.ai/free/en/papers/ferrando-2024-primer-inner-workings-transformer-based/) 9. [**Linear Representations of Sentiment in Large Language Models arXiv:2310.15154**Curt Tigges, Oskar John Hollinsworth, Atticus Geiger, et al.*2023 · 64 citations*](https://md.research.elamur.ai/free/en/papers/tigges-2023-linear-representations-sentiment-large-language/) 10. **[Hopping Too Late: Exploring the Limitations of Large Language Models on Multi-Hop Queries](https://md.research.elamur.ai/free/en/papers/biran-2024-hopping-too-late-exploring-limitations/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Eden Biran, Daniela Gottesman, Sohee Yang, et al.*2024 · 55 citations* 11. **[Information Flow Routes: Automatically Interpreting Language Models at Scale](https://md.research.elamur.ai/free/en/papers/ferrando-2024-information-flow-routes-automatically-interpreting/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Javier Ferrando, Elena Voita*2024 · 43 citations* 12. [**Successor Heads: Recurring, Interpretable Attention Heads In The Wild arXiv:2312.09230**Rhys Gould, Euan Ong, George Ogden, et al.*2023 · 39 citations*](https://md.research.elamur.ai/free/en/papers/gould-2023-successor-heads-recurring-interpretable-attention/) 13. [**AtP*: An efficient and scalable method for localizing LLM behaviour to components arXiv:2403.00745**Janos Kramar, Tom Lieberum, Rohin Shah, et al.*2024 · 32 citations*](https://md.research.elamur.ai/free/en/papers/kramar-2024-atp-efficient-scalable-method-localizing/) 14. [**Copy Suppression: Comprehensively Understanding an Attention Head arXiv:2310.04625**Callum McDougall, Arthur Conmy, Cody Rushing, et al.*2023 · 25 citations*](https://md.research.elamur.ai/free/en/papers/mcdougall-2023-copy-suppression-comprehensively-understanding-attention/) 15. **[Language Models Encode the Value of Numbers Linearly](https://md.research.elamur.ai/free/en/papers/zhu-2025-language-models-encode-value-numbers/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Fangwei Zhu, Damai Dai, Zhifang Sui*2025 · 15 citations* 16. **[The Quest for the Right Mediator: Surveying Mechanistic Interpretability for NLP Through the Lens of Causal Mediation Analysis](https://md.research.elamur.ai/free/en/papers/mueller-2026-quest-right-mediator-surveying-mechanistic/) [Computational Linguistics](https://md.research.elamur.ai/free/en/venues/cl/)**Aaron Mueller, Jannik Brinkmann, Millicent Li, et al.*2026 · 7 citations* 30 more papers of our library cite it; they have no page here yet. - [← back to](https://md.research.elamur.ai/free/en/papers/mcgrath-2023-hydra-effect-emergent-self-repair/) — The Hydra Effect: Emergent Self-repair in Language Model Computations