---
title: "Who cites Is GPT-3 Text Indistinguishable — 62 citing papers"
description: "62 papers of the Elamur Research library cite «Is GPT-3 Text Indistinguishable from Human Text? Scarecrow: A Framework for Scrutinizing…"
canonical: "https://research.elamur.ai/free/en/papers/dou-2022-is-gpt-3-text-indistinguishable/cited-by/"
---
[Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/dou-2022-is-gpt-3-text-indistinguishable/cited-by/)

[home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [Is GPT-3 Text Indistinguishable from Human Text?…](https://md.research.elamur.ai/free/en/papers/dou-2022-is-gpt-3-text-indistinguishable/) / cited by

# Who cites «Is GPT-3 Text Indistinguishable from Human Text? Scarecrow: A Framework for Scrutinizing Machine Text»

62 papers of our library cite it (of the 141,840 whose bibliographies we read) · 6 with a page here, the most cited first · [← back to «Is GPT-3 Text Indistinguishable from Human Text? Scarecrow: A Framework for Scrutinizing Machine Text»](https://md.research.elamur.ai/free/en/papers/dou-2022-is-gpt-3-text-indistinguishable/)

1. [**Fine-Grained Human Feedback Gives Better Rewards for Language Model Training arXiv:2306.01693**Zeqiu Wu, Yushi Hu, Weijia Shi, et al.*2023 · 212 citations*](https://md.research.elamur.ai/free/en/papers/wu-2023-fine-grained-human-feedback-gives/) **[Ghostbuster: Detecting Text Ghostwritten by Large Language Models](https://md.research.elamur.ai/free/en/papers/verma-2024-ghostbuster-detecting-text-ghostwritten-large/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Vivek Verma, Eve Fleisig, Nicholas Tomlin, et al.*2024 · 122 citations* **[How Much Do Language Models Copy From Their Training Data? Evaluating Linguistic Novelty in Text Generation Using RAVEN](https://md.research.elamur.ai/free/en/papers/mccoy-2023-how-much-do-language-models/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**R. Thomas McCoy, Paul Smolensky, Tal Linzen, et al.*2023 · 116 citations* **[LENS: A Learnable Evaluation Metric for Text Simplification](https://md.research.elamur.ai/free/en/papers/maddela-2023-lens-learnable-evaluation-metric-text/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Mounica Maddela, Yao Dou, David Heineman, et al.*2023 · 103 citations*

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

- [← back to](https://md.research.elamur.ai/free/en/papers/dou-2022-is-gpt-3-text-indistinguishable/) — Is GPT-3 Text Indistinguishable from Human Text? Scarecrow: A Framework for Scrutinizing Machine Text