--- title: "Who cites Can we trust the evaluation on — 35 citing papers" description: "35 papers of the Elamur Research library cite «Can we trust the evaluation on ChatGPT?», found in their bibliographies; the most cited first." canonical: "https://research.elamur.ai/free/en/papers/aiyappa-2023-can-we-trust-evaluation-chatgpt/cited-by/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/aiyappa-2023-can-we-trust-evaluation-chatgpt/cited-by/) [home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [Can we trust the evaluation on ChatGPT?](https://md.research.elamur.ai/free/en/papers/aiyappa-2023-can-we-trust-evaluation-chatgpt/) / cited by # Who cites «Can we trust the evaluation on ChatGPT?» 35 papers of our library cite it (of the 149,439 whose bibliographies we read) · 12 with a page here, the most cited first · [← back to «Can we trust the evaluation on ChatGPT?»](https://md.research.elamur.ai/free/en/papers/aiyappa-2023-can-we-trust-evaluation-chatgpt/) 1. **[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* 2. **[Large Language Models Effectively Leverage Document-level Context for Literary Translation, but Critical Errors Persist](https://md.research.elamur.ai/free/en/papers/karpinska-2023-large-language-models-effectively-leverage/) [Conference on Machine Translation (WMT)](https://md.research.elamur.ai/free/en/venues/wmt/)**Marzena Karpinska, Mohit Iyyer*2023 · 156 citations* 3. **[Investigating Data Contamination in Modern Benchmarks for Large Language Models](https://md.research.elamur.ai/free/en/papers/deng-2024-investigating-data-contamination-modern-benchmarks/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Chunyuan Deng, Yilun Zhao, Xiangru Tang, et al.*2024 · 137 citations* 4. **[TrueTeacher: Learning Factual Consistency Evaluation with Large Language Models](https://md.research.elamur.ai/free/en/papers/gekhman-2023-trueteacher-learning-factual-consistency-evaluation/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Zorik Gekhman, Jonathan Herzig, Roee Aharoni, et al.*2023 · 106 citations* 5. **[GPTEval: A Survey on Assessments of ChatGPT and GPT-4](https://md.research.elamur.ai/free/en/papers/mao-2024-gpteval-survey-assessments-chatgpt-gpt/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Rui Mao, Guanyi Chen, Xulang Zhang, et al.*2024 · 75 citations* 6. [**Shepherd: A Critic for Language Model Generation arXiv:2308.04592**Tianlu Wang, Ping Yu, Xiaoqing Ellen Tan, et al.*2023 · 60 citations*](https://md.research.elamur.ai/free/en/papers/wang-2023-shepherd-critic-language-model-generation/) 7. **[Automated stance detection in complex topics and small languages: the challenging case of immigration in polarizing news media](https://md.research.elamur.ai/free/en/papers/mets-2023-automated-stance-detection-complex-topics/) [PLoS ONE](https://md.research.elamur.ai/free/en/venues/plos-one/)**Mark Mets, Andres Karjus, Indrek Ibrus, et al.*2023 · 43 citations* 8. **[AutomaTikZ: Text-Guided Synthesis of Scientific Vector Graphics with TikZ](https://md.research.elamur.ai/free/en/papers/belouadi-2023-automatikz-text-guided-synthesis-scientific/) [International Conference on Learning Representations (ICLR)](https://md.research.elamur.ai/free/en/venues/international-conference-on-learning-representations-iclr/)**Jonas Belouadi, Anne Lauscher, Steffen Eger*2023 · 31 citations* 9. [**Prompting and Fine-Tuning Open-Sourced Large Language Models for Stance Classification arXiv:2309.13734**Iain J. Cruickshank, Lynnette Hui Xian Ng*2023 · 18 citations*](https://md.research.elamur.ai/free/en/papers/cruickshank-2023-prompting-fine-tuning-open-sourced/) 10. **[MGKM at StanceEval2024 Fine-Tuning Large Language Models for Arabic Stance Detection](https://md.research.elamur.ai/free/en/papers/alghaslan-2024-mgkm-stanceeval2024-fine-tuning-large/) [Arabic Natural Language Processing Conference (ArabicNLP)](https://md.research.elamur.ai/free/en/venues/arabicnlp/)**Mamoun Alghaslan, Khaled Almutairy*2024 · 7 citations* 11. **[Can a Large Language Model Replace Humans at Rating Lexical Semantic Relations Strength?](https://md.research.elamur.ai/free/en/papers/santos-2026-can-large-language-model-replace/) [Computational Linguistics](https://md.research.elamur.ai/free/en/venues/cl/)**André Fernandes dos Santos, José Paulo Leal*2026 · 1 citation* 12. **[Identifying the Achilles' Heel: An Iterative Method for Uncovering Factual Errors in Large Language Models](https://md.research.elamur.ai/free/en/papers/wang-2026-identifying-achilles-heel-iterative-method/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Wenxuan Wang, Yuk-Kit Chan, Zixuan Ling, et al.*2026* 23 more papers of our library cite it; they have no page here yet. - [← back to](https://md.research.elamur.ai/free/en/papers/aiyappa-2023-can-we-trust-evaluation-chatgpt/) — Can we trust the evaluation on ChatGPT?