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Who cites «Length Generalization in Arithmetic Transformers»

27 papers of our library cite it (of the 149,439 whose bibliographies we read) · 12 with a page here, the most cited first · ← back to «Length Generalization in Arithmetic Transformers»

  1. What Algorithms can Transformers Learn? A Study in Length GeneralizationarXiv:2310.16028Hattie Zhou, Arwen Bradley, Etai Littwin, et al.2023 · 67 citations
  2. Physics of Language Models: Part 2.1, Grade-School Math and the Hidden Reasoning ProcessarXiv:2407.20311Tian Ye, Zicheng Xu, Yuanzhi Li, et al.2024 · 58 citations
  3. Repeat After Me: Transformers are Better than State Space Models at CopyingarXiv:2402.01032Samy Jelassi, David Brandfonbrener, Sham M. Kakade, et al.2024 · 57 citations
  4. GPT Can Solve Mathematical Problems Without a CalculatorarXiv:2309.03241Zhen Yang, Ming Ding, Qingsong Lv, et al.2023 · 41 citations
  5. Positional Description Matters for Transformers ArithmeticarXiv:2311.14737Ruoqi Shen, Sébastien Bubeck, Ronen Eldan, et al.2023 · 30 citations
  6. Transformers Can Achieve Length Generalization But Not RobustlyarXiv:2402.09371Yongchao Zhou, Uri Alon, Xinyun Chen, et al.2024 · 29 citations
  7. Chain-of-Thought Reasoning is a Policy Improvement OperatorarXiv:2309.08589Hugh Zhang, David C. Parkes2023 · 11 citations
  8. SNIP: Bridging Mathematical Symbolic and Numeric Realms with Unified Pre-trainingarXiv:2310.02227Kazem Meidani, Parshin Shojaee, Chandan K. Reddy, et al.2023 · 8 citations
  9. Improving Length-Generalization in Transformers via Task HintingarXiv:2310.00726Pranjal Awasthi, Anupam Gupta2023 · 7 citations
  10. Explicitly Encoding Structural Symmetry is Key to Length Generalization in Arithmetic TasksarXiv:2406.01895Mahdi Sabbaghi, George Pappas, Hamed Hassani, et al.2024 · 5 citations

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

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