---
title: "Who cites LLMs and the Abstraction and — 27 citing papers"
description: "27 papers of the Elamur Research library cite «LLMs and the Abstraction and Reasoning Corpus: Successes, Failures, and the Importance of…"
canonical: "https://research.elamur.ai/free/en/papers/xu-2023-llms-abstraction-reasoning-corpus-successes/cited-by/"
---
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# Who cites «LLMs and the Abstraction and Reasoning Corpus: Successes, Failures, and the Importance of Object-based Representations»

27 papers of our library cite it (of the 149,439 whose bibliographies we read) · 3 with a page here, the most cited first · [← back to «LLMs and the Abstraction and Reasoning Corpus: Successes, Failures, and the Importance of Object-based Representations»](https://md.research.elamur.ai/free/en/papers/xu-2023-llms-abstraction-reasoning-corpus-successes/)

1. [**Large Language Models as General Pattern Machines arXiv:2307.04721**Suvir Mirchandani, Fei Xia, Pete Florence, et al.*2023 · 88 citations*](https://md.research.elamur.ai/free/en/papers/mirchandani-2023-large-language-models-general-pattern/)
2. **[Reasoning Abilities of Large Language Models: In-Depth Analysis on the Abstraction and Reasoning Corpus](https://md.research.elamur.ai/free/en/papers/lee-2024-reasoning-abilities-large-language-models/) [ACM Transactions on Intelligent Systems and Technology](https://md.research.elamur.ai/free/en/venues/acm-transactions-on-intelligent-systems-and-technology/)**Seungpil Lee, Woochang Sim, Donghyeon Shin, et al.*2024 · 38 citations*
3. **[The Thin Line Between Comprehension and Persuasion in LLMs](https://md.research.elamur.ai/free/en/papers/wynter-2026-thin-line-between-comprehension-persuasion/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Adrian de Wynter, Tangming Yuan*2026 · 1 citation*

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

- [← back to](https://md.research.elamur.ai/free/en/papers/xu-2023-llms-abstraction-reasoning-corpus-successes/) — LLMs and the Abstraction and Reasoning Corpus: Successes, Failures, and the Importance of Object-based Representations
