---
title: "Who cites Yao Dou — 143 papers of our library"
description: "143 papers of the Elamur Research library cite the works of Yao Dou, found in their bibliographies; the most cited first."
canonical: "https://research.elamur.ai/free/en/authors/yao-dou/cited-by/"
---
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# Who cites Yao Dou

149 citations of their works from 143 papers of our library (of the 141,840 whose bibliographies we read) · 10 with a page here, the most cited first · [← Yao Dou](https://md.research.elamur.ai/free/en/authors/yao-dou/)

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* **[A Human-in/on-the-Loop Framework for Accessible Text Generation](https://md.research.elamur.ai/free/en/papers/moreno-2026-human-loop-framework-accessible-text/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Lourdes Moreno, Paloma Martínez*2026 · 3 citations* **[Assessing Small Language Models as Text Simplification Evaluators](https://md.research.elamur.ai/free/en/papers/navarrete-2026-assessing-small-language-models-as/) [Workshop on Evaluating Text Difficulty in a Multilingual Context](https://md.research.elamur.ai/free/en/venues/determit/)**David Carranza Navarrete, Jan Bakker, Jaap Kamps*2026* [**Exploring Cognitively Informed Sentence Simplification with Gaze-Guided Text Generation Proceedings fo the Second International Workshop on Eye-Tracking Resources and Evaluation for Human-Aligned NLP**Andreas Säuberli, Diego Frassinelli, Barbara Plank*2026*](https://md.research.elamur.ai/free/en/papers/sauberli-2026-exploring-cognitively-informed-sentence-simplification/) **[Simplify-Pro: A Two-level and Progressive LLM-based Framework for Auto Long Text Simplification](https://md.research.elamur.ai/free/en/papers/zhou-2026-simplify-pro-two-level-progressive/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Peng Zhou, Guangxin Li, Xiaoying Huang, et al.*2026*

133 more citing papers of our library have no page here yet.

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