---
title: "Who cites End-to-end Algorithm Synthesis — 9 citing papers"
description: "9 papers of the Elamur Research library cite «End-to-end Algorithm Synthesis with Recurrent Networks: Logical Extrapolation Without…"
canonical: "https://research.elamur.ai/free/en/papers/bansal-2022-end-end-algorithm-synthesis-recurrent/cited-by/"
---
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# Who cites «End-to-end Algorithm Synthesis with Recurrent Networks: Logical Extrapolation Without Overthinking»

9 papers of our library cite it (of the 149,439 whose bibliographies we read) · 4 with a page here, the most cited first · [← back to «End-to-end Algorithm Synthesis with Recurrent Networks: Logical Extrapolation Without Overthinking»](https://md.research.elamur.ai/free/en/papers/bansal-2022-end-end-algorithm-synthesis-recurrent/)

1. [**Exploring Length Generalization in Large Language Models arXiv:2207.04901**Cem Anil, Yuhuai Wu, Anders Andreassen, et al.*2022 · 139 citations*](https://md.research.elamur.ai/free/en/papers/anil-2022-exploring-length-generalization-large-language/)
2. [**Neural Networks and the Chomsky Hierarchy arXiv:2207.02098**Grégoire Delétang, Anian Ruoss, Jordi Grau-Moya, et al.*2022 · 112 citations*](https://md.research.elamur.ai/free/en/papers/deletang-2022-neural-networks-chomsky-hierarchy/)
3. **[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*
4. [**Length Generalization in Arithmetic Transformers arXiv:2306.15400**Samy Jelassi, Stéphane d'Ascoli, Carles Domingo-Enrich, et al.*2023 · 29 citations*](https://md.research.elamur.ai/free/en/papers/jelassi-2023-length-generalization-arithmetic-transformers/)

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

- [← back to](https://md.research.elamur.ai/free/en/papers/bansal-2022-end-end-algorithm-synthesis-recurrent/) — End-to-end Algorithm Synthesis with Recurrent Networks: Logical Extrapolation Without Overthinking