--- title: "Who cites Human-like Summarization Evaluation with ChatGPT" description: "92 papers of the Elamur Research library cite «Human-like Summarization Evaluation with ChatGPT», found in their bibliographies; the most…" canonical: "https://research.elamur.ai/free/en/papers/gao-2023-human-like-summarization-evaluation-chatgpt/cited-by/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/gao-2023-human-like-summarization-evaluation-chatgpt/cited-by/) [home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [Human-like Summarization Evaluation with ChatGPT](https://md.research.elamur.ai/free/en/papers/gao-2023-human-like-summarization-evaluation-chatgpt/) / cited by # Who cites «Human-like Summarization Evaluation with ChatGPT» 92 papers of our library cite it (of the 149,439 whose bibliographies we read) · 21 with a page here, the most cited first · [← back to «Human-like Summarization Evaluation with ChatGPT»](https://md.research.elamur.ai/free/en/papers/gao-2023-human-like-summarization-evaluation-chatgpt/) 1. **[A Survey on Hallucination in Large Language Models: Principles, Taxonomy, Challenges, and Open Questions](https://md.research.elamur.ai/free/en/papers/huang-2023-survey-hallucination-large-language-models/) [ACM Transactions on Information Systems](https://md.research.elamur.ai/free/en/venues/acm-transactions-on-information-systems/)**Lei Huang, Weijiang Yu, Weitao Ma, et al.*2023 · 3,231 citations* 2. **[A Survey of Large Language Models](https://md.research.elamur.ai/free/en/papers/zhao-2023-survey-large-language-models/) [Frontiers of Computer Science](https://md.research.elamur.ai/free/en/venues/frontiers-of-computer-science/)**Wayne Xin Zhao, Kun Zhou, Junyi Li, et al.*2023 · 2,875 citations* 3. [**ChatEval: Towards Better LLM-based Evaluators through Multi-Agent Debate arXiv:2308.07201**Chi-Min Chan, Weize Chen, Yusheng Su, et al.*2023 · 359 citations*](https://md.research.elamur.ai/free/en/papers/chan-2023-chateval-better-llm-based/) 4. **[AlignScore: Evaluating Factual Consistency with A Unified Alignment Function](https://md.research.elamur.ai/free/en/papers/zha-2023-alignscore-evaluating-factual-consistency-unified/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yuheng Zha, Yichi Yang, Ruichen Li, et al.*2023 · 284 citations* 5. **[Large Language Models for Data Annotation and Synthesis: A Survey](https://md.research.elamur.ai/free/en/papers/tan-2024-large-language-models-data-annotation/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Zhen Tan, Dawei Li, Song Wang, et al.*2024 · 262 citations* 6. [**Jais and Jais-chat: Arabic-Centric Foundation and Instruction-Tuned Open Generative Large Language Models arXiv:2308.16149**Neha Sengupta, Sunil Kumar Sahu, Bokang Jia, et al.*2023 · 218 citations*](https://md.research.elamur.ai/free/en/papers/sengupta-2023-jais-jais-chat-arabic-centric/) 7. [**Aligning Large Language Models with Human: A Survey arXiv:2307.12966**Yufei Wang, Wanjun Zhong, Liangyou Li, et al.*2023 · 202 citations*](https://md.research.elamur.ai/free/en/papers/wang-2023-aligning-large-language-models-human/) 8. **[A Systematic Study and Comprehensive Evaluation of ChatGPT on Benchmark Datasets](https://md.research.elamur.ai/free/en/papers/laskar-2023-systematic-study-comprehensive-evaluation-chatgpt/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Md Tahmid Rahman Laskar, M Saiful Bari, Mizanur Rahman, et al.*2023 · 200 citations* 9. [**The Prompt Report: A Systematic Survey of Prompt Engineering Techniques arXiv:2406.06608**Sander Schulhoff, Michael Ilie, Nishant Balepur, et al.*2024 · 189 citations*](https://md.research.elamur.ai/free/en/papers/schulhoff-2024-prompt-report-systematic-survey-prompt/) 10. **[LLM-based NLG Evaluation: Current Status and Challenges](https://md.research.elamur.ai/free/en/papers/gao-2025-llm-based-nlg-evaluation-current/) [Computational Linguistics](https://md.research.elamur.ai/free/en/venues/cl/)**Mingqi Gao, Xinyu Hu, Xunjian Yin, et al.*2025 · 153 citations* 11. **[UniChart: A Universal Vision-language Pretrained Model for Chart Comprehension and Reasoning](https://md.research.elamur.ai/free/en/papers/masry-2023-unichart-universal-vision-language-pretrained/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Ahmed Masry, Parsa Kavehzadeh, Xuan Long Do, et al.*2023 · 121 citations* 12. **[Large Language Models are Not Yet Human-Level Evaluators for Abstractive Summarization](https://md.research.elamur.ai/free/en/papers/shen-2023-large-language-models-are-not/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Chenhui Shen, Liying Cheng, Xuan-Phi Nguyen, et al.*2023 · 119 citations* 13. **[Benchmarking Foundation Models with Language-Model-as-an-Examiner](https://md.research.elamur.ai/free/en/papers/bai-2023-benchmarking-foundation-models-language-model/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Yushi Bai, Jiahao Ying, Yixin Cao, et al.*2023 · 106 citations* 14. **[A Systematic Survey and Critical Review on Evaluating Large Language Models: Challenges, Limitations, and Recommendations](https://md.research.elamur.ai/free/en/papers/laskar-2024-systematic-survey-critical-review-evaluating/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Md Tahmid Rahman Laskar, Sawsan Alqahtani, M Saiful Bari, et al.*2024 · 105 citations* 15. **[On Learning to Summarize with Large Language Models as References](https://md.research.elamur.ai/free/en/papers/liu-2024-learning-summarize-large-language-models/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Yixin Liu, Kejian Shi, Katherine He, et al.*2024 · 94 citations* 16. **[FineSurE: Fine-grained Summarization Evaluation using LLMs](https://md.research.elamur.ai/free/en/papers/song-2024-finesure-fine-grained-summarization-evaluation/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Hwanjun Song, Hang Su, Igor Shalyminov, et al.*2024 · 92 citations* 17. [**Large Language Models are Inconsistent and Biased Evaluators arXiv:2405.01724**Rickard Stureborg, Dimitris Alikaniotis, Yoshi Suhara*2024 · 91 citations*](https://md.research.elamur.ai/free/en/papers/stureborg-2024-large-language-models-inconsistent-biased/) 18. **[Leveraging Large Language Models for NLG Evaluation: Advances and Challenges](https://md.research.elamur.ai/free/en/papers/li-2024-leveraging-large-language-models-nlg/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Zhen Li, Xiaohan Xu, Tao Shen, et al.*2024 · 63 citations* 19. **[AraHalluEval: A Fine-grained Hallucination Evaluation Framework for Arabic LLMs](https://md.research.elamur.ai/free/en/papers/alansari-2025-arahallueval-fine-grained-hallucination-evaluation/) [Arabic Natural Language Processing Conference (ArabicNLP)](https://md.research.elamur.ai/free/en/venues/arabicnlp/)**Aisha Alansari, Hamzah Luqman*2025 · 9 citations* 20. **[Quantifying and Improving the Robustness of Retrieval-Augmented Language Models Against Spurious Features in Grounding Data](https://md.research.elamur.ai/free/en/papers/yang-2026-quantifying-improving-robustness-retrieval-augmented/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Shiping Yang, Jie Wu, Wenbiao Ding, et al.*2026* 21. **[Survey on Hallucinations in Large Language Models (大语言模型的幻觉问题研究综述)](https://md.research.elamur.ai/free/en/papers/liu-2024-hallucinations-large-language/) [Journal of Software](https://md.research.elamur.ai/free/en/venues/journal-of-software/)**Zeyuan Liu (刘泽垣), Pengjiang Wang (王鹏江), Xiaobin Song (宋晓斌), et al.*2024* 71 more papers of our library cite it; they have no page here yet. - [← back to](https://md.research.elamur.ai/free/en/papers/gao-2023-human-like-summarization-evaluation-chatgpt/) — Human-like Summarization Evaluation with ChatGPT