🔗 Who cites «Copy Suppression: Comprehensively Understanding an Attention Head»

23 papers of our library cite it (of the 149,439 whose bibliographies we read) · 8 with a page here, the most cited first · ← back to «Copy Suppression: Comprehensively Understanding an Attention Head»

1. Mechanistic Interpretability for AI Safety — A ReviewarXiv:2404.14082Leonard Bereska, Efstratios Gavves2024 · 108 citations
2. Foundational Challenges in Assuring Alignment and Safety of Large Language ModelsarXiv:2404.09932Usman Anwar, Abulhair Saparov, Javier Rando, et al.2024 · 87 citations
3. A Primer on the Inner Workings of Transformer-based Language ModelsarXiv:2405.00208Javier Ferrando, Gabriele Sarti, Arianna Bisazza, et al.2024 · 72 citations
4. A Practical Review of Mechanistic Interpretability for Transformer-Based Language ModelsarXiv:2407.02646Daking Rai, Yilun Zhou, Shi Feng, et al.2024 · 58 citations
5. Arithmetic Without Algorithms: Language Models Solve Math With a Bag of HeuristicsarXiv:2410.21272Yaniv Nikankin, Anja Reusch, Aaron Mueller, et al.2024 · 51 citations
6. Successor Heads: Recurring, Interpretable Attention Heads In The WildarXiv:2312.09230Rhys Gould, Euan Ong, George Ogden, et al.2023 · 39 citations
7. AtP*: An efficient and scalable method for localizing LLM behaviour to componentsarXiv:2403.00745Janos Kramar, Tom Lieberum, Rohin Shah, et al.2024 · 32 citations
8. Competition of Mechanisms: Tracing How Language Models Handle Facts and CounterfactualsAnnual Meeting of the Association for Computational Linguistics (ACL)Francesco Ortu, Zhijing Jin, Diego Doimo, et al.2024 · 23 citations

15 more papers of our library cite it; they have no page here yet.

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