🔗 Who cites «Linear attention is (maybe) all you need (to understand transformer optimization)»

9 papers of our library cite it (of the 149,439 whose bibliographies we read) · 2 with a page here, the most cited first · ← back to «Linear attention is (maybe) all you need (to understand transformer optimization)»

1. Transformers learn to implement preconditioned gradient descent for in-context learningConference on Neural Information Processing Systems (NeurIPS)Kwangjun Ahn, Xiang Cheng, Hadi Daneshmand, et al.2023 · 37 citations
2. Explicitly Encoding Structural Symmetry is Key to Length Generalization in Arithmetic TasksarXiv:2406.01895Mahdi Sabbaghi, George Pappas, Hamed Hassani, et al.2024 · 5 citations

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

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