---
title: "Who cites Positional Description Matters for — 27 citing papers"
description: "27 papers of the Elamur Research library cite «Positional Description Matters for Transformers Arithmetic», found in their bibliographies; the…"
canonical: "https://research.elamur.ai/free/en/papers/shen-2023-positional-description-matters-transformers-arithmetic/cited-by/"
---
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[home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [Positional Description Matters for Transformers…](https://md.research.elamur.ai/free/en/papers/shen-2023-positional-description-matters-transformers-arithmetic/) / cited by

# Who cites «Positional Description Matters for Transformers Arithmetic»

27 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 «Positional Description Matters for Transformers Arithmetic»](https://md.research.elamur.ai/free/en/papers/shen-2023-positional-description-matters-transformers-arithmetic/)

1. **[On Context Utilization in Summarization with Large Language Models](https://md.research.elamur.ai/free/en/papers/ravaut-2024-context-utilization-summarization-large-language/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Mathieu Ravaut, Aixin Sun, Nancy Chen, et al.*2024 · 67 citations*
2. [**Repeat After Me: Transformers are Better than State Space Models at Copying arXiv:2402.01032**Samy Jelassi, David Brandfonbrener, Sham M. Kakade, et al.*2024 · 57 citations*](https://md.research.elamur.ai/free/en/papers/jelassi-2024-repeat-after-me-transformers-better/)
3. [**The pitfalls of next-token prediction arXiv:2403.06963**Gregor Bachmann, Vaishnavh Nagarajan*2024 · 39 citations*](https://md.research.elamur.ai/free/en/papers/bachmann-2024-pitfalls-next-token-prediction/)
4. **[Transformers Can Do Arithmetic with the Right Embeddings](https://md.research.elamur.ai/free/en/papers/mcleish-2024-transformers-arithmetic-right-embeddings/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Sean McLeish, Arpit Bansal, Alex Stein, et al.*2024 · 36 citations*
5. [**Transformers Can Achieve Length Generalization But Not Robustly arXiv:2402.09371**Yongchao Zhou, Uri Alon, Xinyun Chen, et al.*2024 · 29 citations*](https://md.research.elamur.ai/free/en/papers/zhou-2024-transformers-achieve-length-generalization-but/)
6. **[NumeroLogic: Number Encoding for Enhanced LLMs' Numerical Reasoning](https://md.research.elamur.ai/free/en/papers/schwartz-2024-numerologic-number-encoding-enhanced-llms/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Eli Schwartz, Leshem Choshen, Joseph Shtok, et al.*2024 · 26 citations*
7. [**Do language models plan ahead for future tokens? arXiv:2404.00859**Wilson Wu, John X. Morris, Lionel Levine*2024 · 10 citations*](https://md.research.elamur.ai/free/en/papers/wu-2024-language-models-plan-ahead-future/)
8. [**Explicitly Encoding Structural Symmetry is Key to Length Generalization in Arithmetic Tasks arXiv:2406.01895**Mahdi Sabbaghi, George Pappas, Hamed Hassani, et al.*2024 · 5 citations*](https://md.research.elamur.ai/free/en/papers/sabbaghi-2024-explicitly-encoding-structural-symmetry-key/)

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

- [← back to](https://md.research.elamur.ai/free/en/papers/shen-2023-positional-description-matters-transformers-arithmetic/) — Positional Description Matters for Transformers Arithmetic