---
title: "Who cites Communicating Natural Programs — 18 citing papers"
description: "18 papers of the Elamur Research library cite «Communicating Natural Programs to Humans and Machines», found in their bibliographies…"
canonical: "https://research.elamur.ai/free/en/papers/acquaviva-2021-communicating-natural-programs-humans-machines/cited-by/"
---
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# Who cites «Communicating Natural Programs to Humans and Machines»

18 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 «Communicating Natural Programs to Humans and Machines»](https://md.research.elamur.ai/free/en/papers/acquaviva-2021-communicating-natural-programs-humans-machines/)

1. **[Large Language Model Instruction Following: A Survey of Progresses and Challenges](https://md.research.elamur.ai/free/en/papers/lou-2024-large-language-model-instruction-following/) [Computational Linguistics](https://md.research.elamur.ai/free/en/venues/cl/)**Renze Lou, Kai Zhang, Wenpeng Yin*2024 · 83 citations*
2. [**Large Language Models Are Not Strong Abstract Reasoners arXiv:2305.19555**Gael Gendron, Qiming Bao, Michael Witbrock, et al.*2023 · 61 citations*](https://md.research.elamur.ai/free/en/papers/gendron-2023-large-language-models-strong-abstract/)
3. **[Parsel: Algorithmic Reasoning with Language Models by Composing Decompositions](https://md.research.elamur.ai/free/en/papers/zelikman-2023-parsel-algorithmic-reasoning-language-models/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Eric Zelikman, Qian Huang, Gabriel Poesia, et al.*2023 · 56 citations*
4. **[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*
5. [**The Surprising Effectiveness of Test-Time Training for Few-Shot Learning arXiv:2411.07279**Ekin Akyürek, Mehul Damani, Adam Zweiger, et al.*2024 · 36 citations*](https://md.research.elamur.ai/free/en/papers/akyurek-2024-surprising-effectiveness-test-time-training/)
6. [**LLMs and the Abstraction and Reasoning Corpus: Successes, Failures, and the Importance of Object-based Representations arXiv:2305.18354**Yudong Xu, Wenhao Li, Pashootan Vaezipoor, et al.*2023 · 32 citations*](https://md.research.elamur.ai/free/en/papers/xu-2023-llms-abstraction-reasoning-corpus-successes/)
7. [**Evaluating statistical language models as pragmatic reasoners arXiv:2305.01020**Benjamin Lipkin, Lionel Wong, Gabriel Grand, et al.*2023 · 18 citations*](https://md.research.elamur.ai/free/en/papers/lipkin-2023-evaluating-statistical-language-models-pragmatic/)
8. [**H-ARC: A Robust Estimate of Human Performance on the Abstraction and Reasoning Corpus Benchmark arXiv:2409.01374**Solim LeGris, Wai Keen Vong, Brenden M. Lake, et al.*2024 · 12 citations*](https://md.research.elamur.ai/free/en/papers/legris-2024-h-arc-robust-estimate-human/)

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

- [← back to](https://md.research.elamur.ai/free/en/papers/acquaviva-2021-communicating-natural-programs-humans-machines/) — Communicating Natural Programs to Humans and Machines