---
title: "Who cites Evaluating Transformer Language — 12 citing papers"
description: "12 papers of the Elamur Research library cite «Evaluating Transformer Language Models on Arithmetic Operations Using Number…"
canonical: "https://research.elamur.ai/free/en/papers/muffo-2023-evaluating-transformer-language-models-arithmetic/cited-by/"
---
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# Who cites «Evaluating Transformer Language Models on Arithmetic Operations Using Number Decomposition»

12 papers of our library cite it (of the 149,439 whose bibliographies we read) · 6 with a page here, the most cited first · [← back to «Evaluating Transformer Language Models on Arithmetic Operations Using Number Decomposition»](https://md.research.elamur.ai/free/en/papers/muffo-2023-evaluating-transformer-language-models-arithmetic/)

1. [**Simple synthetic data reduces sycophancy in large language models arXiv:2308.03958**Jerry Wei, Da Huang, Yifeng Lu, et al.*2023 · 134 citations*](https://md.research.elamur.ai/free/en/papers/wei-2023-simple-synthetic-data-reduces-sycophancy/)
2. [**How well do Large Language Models perform in Arithmetic tasks? arXiv:2304.02015**Zheng Yuan, Hongyi Yuan, Chuanqi Tan, et al.*2023 · 93 citations*](https://md.research.elamur.ai/free/en/papers/yuan-2023-well-large-language-models-perform/)
3. [**Goat: Fine-tuned LLaMA Outperforms GPT-4 on Arithmetic Tasks arXiv:2305.14201**Tiedong Liu, Bryan Kian Hsiang Low*2023 · 65 citations*](https://md.research.elamur.ai/free/en/papers/liu-2023-goat-fine-tuned-llama-outperforms/)
4. [**Tokenization counts: the impact of tokenization on arithmetic in frontier LLMs arXiv:2402.14903**Aaditya K. Singh, DJ Strouse*2024 · 55 citations*](https://md.research.elamur.ai/free/en/papers/singh-2024-tokenization-counts-impact-tokenization-arithmetic/)
5. **[Exploring the Numerical Reasoning Capabilities of Language Models: A Comprehensive Analysis on Tabular Data](https://md.research.elamur.ai/free/en/papers/akhtar-2023-exploring-numerical-reasoning-capabilities-language/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Mubashara Akhtar, Abhilash Shankarampeta, Vivek Gupta, et al.*2023 · 38 citations*
6. **[Tokenisation is NP-Complete](https://md.research.elamur.ai/free/en/papers/whittington-2025-tokenisation-is-np-complete/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Philip Whittington, Gregor Bachmann, Tiago Pimentel*2025 · 4 citations*

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

- [← back to](https://md.research.elamur.ai/free/en/papers/muffo-2023-evaluating-transformer-language-models-arithmetic/) — Evaluating Transformer Language Models on Arithmetic Operations Using Number Decomposition