---
title: "Who cites Hongyuan Lu"
description: "76 papers of the Elamur Research library cite the works of Hongyuan Lu, found in their bibliographies; the most cited first."
canonical: "https://research.elamur.ai/free/en/authors/hongyuan-lu/cited-by/"
---
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# Who cites Hongyuan Lu

83 citations of their works from 76 papers of our library (of the 140,884 whose bibliographies we read) · 11 with a page here, the most cited first · [← Hongyuan Lu](https://md.research.elamur.ai/free/en/authors/hongyuan-lu/)

1. [**Document-Level Machine Translation with Large Language Models**Longyue Wang, Chenyang Lyu, Tianbo Ji, et al.*2023 · 295 citations*](https://md.research.elamur.ai/free/en/papers/wang-2023-document-level-machine-translation-large/)
2. [**Exploring Human-Like Translation Strategy with Large Language Models**Zhiwei He, Tian Liang, Wenxiang Jiao, et al.*2024 · 207 citations*](https://md.research.elamur.ai/free/en/papers/he-2024-exploring-human-like-translation-strategy/)
3. [**Towards Making the Most of ChatGPT for Machine Translation**Keqin Peng, Liang Ding, Qihuang Zhong, et al.*2023 · 190 citations*](https://md.research.elamur.ai/free/en/papers/peng-2023-making-most-chatgpt-machine-translation/)
4. [**The Prompt Report: A Systematic Survey of Prompt Engineering Techniques**Sander Schulhoff, Michael Ilie, Nishant Balepur, et al.*2024 · 187 citations*](https://md.research.elamur.ai/free/en/papers/schulhoff-2024-prompt-report-systematic-survey-prompt/)
5. [**Large Language Models Effectively Leverage Document-level Context for Literary Translation, but Critical Errors Persist**Marzena Karpinska, Mohit Iyyer*2023 · 156 citations*](https://md.research.elamur.ai/free/en/papers/karpinska-2023-large-language-models-effectively-leverage/)
6. [**TARJAMAT: Evaluation of Bard and ChatGPT on Machine Translation of Ten Arabic Varieties**Karima Kadaoui, Samar M. Magdy, Abdul Waheed, et al.*2023 · 60 citations*](https://md.research.elamur.ai/free/en/papers/kadaoui-2023-tarjamat-evaluation-bard-chatgpt-machine/)
7. [**Can Linguistically Related Languages Guide LLM Translation in Low-Resource Settings?**Aishwarya Ramasethu, Rohin Garg, Niyathi Allu, et al.*2026 · 1 citation*](https://md.research.elamur.ai/free/en/papers/ramasethu-2026-can-linguistically-related-languages-guide/)
8. [**Benchmark Data Contamination in Underrepresented Languages: A Comprehensive Analysis Using Brazilian Data**Iriedson Souto Maior de Moraes Vilar, David Candeia Maia, João Brunet, et al.*2026*](https://md.research.elamur.ai/free/en/papers/vilar-2026-benchmark-data-contamination-underrepresented-languages/)
9. [**GlossMATE: Multi-Agent Translator Explanations for Glosses**Changbing Yang, Patrick Littell, Gabriel Bernier-Colborne, et al.*2026*](https://md.research.elamur.ai/free/en/papers/yang-2026-glossmate-multi-agent-translator-explanations/)
10. [**The MaTOS Pipeline for the Translation of Scientific Abstracts on the HAL Platform**Panagiotis Tsolakis, Ziqian Peng, Laurent Romary, et al.*2026*](https://md.research.elamur.ai/free/en/papers/tsolakis-2026-matos-pipeline-translation-scientific-abstracts/)
11. [**Toxic Subword Pruning for Dialogue Response Generation on Large Language Models**Hongyuan Adam Lu, Wai Lam*2026*](https://md.research.elamur.ai/free/en/papers/lu-2026-toxic-subword-pruning-dialogue-response/)

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

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