--- title: "Who cites Nancy Fulda — 278 papers of our library" description: "278 papers of the Elamur Research library cite the works of Nancy Fulda, found in their bibliographies; the most cited first." canonical: "https://research.elamur.ai/free/en/authors/nancy-fulda/cited-by/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/nancy-fulda/cited-by/) [home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / [Nancy Fulda](https://md.research.elamur.ai/free/en/authors/nancy-fulda/) / cited by # Who cites Nancy Fulda 278 citations of their works from 278 papers of our library (of the 141,840 whose bibliographies we read) · 22 with a page here, the most cited first · [← Nancy Fulda](https://md.research.elamur.ai/free/en/authors/nancy-fulda/) 1. [**A Survey on In-context Learning arXiv:2301.00234**Qingxiu Dong, Lei Li, Damai Dai, et al.*2023 · 959 citations*](https://md.research.elamur.ai/free/en/papers/dong-2023-survey-context-learning/) **[Can Large Language Models Transform Computational Social Science?](https://md.research.elamur.ai/free/en/papers/ziems-2023-large-language-models-transform-computational/) [Computational Linguistics](https://md.research.elamur.ai/free/en/venues/cl/)**Caleb Ziems, William Held, Omar Shaikh, et al.*2023 · 777 citations* **[AlpacaFarm: A Simulation Framework for Methods that Learn from Human Feedback](https://md.research.elamur.ai/free/en/papers/dubois-2023-alpacafarm-simulation-framework-methods-that/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Yann Dubois, Xuechen Li, Rohan Taori, et al.*2023 · 424 citations* **[Security and Privacy Challenges of Large Language Models: A Survey](https://md.research.elamur.ai/free/en/papers/das-2024-security-privacy-challenges-large-language/) [ACM Computing Surveys](https://md.research.elamur.ai/free/en/venues/acm-computing-surveys/)**Badhan Chandra Das, M. Hadi Amini, Yanzhao Wu*2024 · 422 citations* [**Whose Opinions Do Language Models Reflect? arXiv:2303.17548**Shibani Santurkar, Esin Durmus, Faisal Ladhak, et al.*2023 · 392 citations*](https://md.research.elamur.ai/free/en/papers/santurkar-2023-whose-opinions-language-models-reflect/) **[From Pretraining Data to Language Models to Downstream Tasks: Tracking the Trails of Political Biases Leading to Unfair NLP Models](https://md.research.elamur.ai/free/en/papers/feng-2023-pretraining-data-language-models-downstream/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Shangbin Feng, Chan Young Park, Yuhan Liu, et al.*2023 · 306 citations* [**Challenges and Applications of Large Language Models arXiv:2307.10169**Jean Kaddour, Joshua Harris, Maximilian Mozes, et al.*2023 · 300 citations*](https://md.research.elamur.ai/free/en/papers/kaddour-2023-challenges-applications-large-language-models/) [**Prompting Large Language Model for Machine Translation: A Case Study arXiv:2301.07069**Biao Zhang, Barry Haddow, Alexandra Birch*2023 · 293 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2023-prompting-large-language-model-machine/) [**ChatGPT-4 Outperforms Experts and Crowd Workers in Annotating Political Twitter Messages with Zero-Shot Learning arXiv:2304.06588**Petter Tornberg*2023 · 231 citations*](https://md.research.elamur.ai/free/en/papers/tornberg-2023-chatgpt-4-outperforms-experts-crowd/) [**The Prompt Report: A Systematic Survey of Prompt Engineering Techniques arXiv:2406.06608**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/) [**Leveraging Large Language Models for Multiple Choice Question Answering arXiv:2210.12353**Joshua Robinson, Christopher Michael Rytting, David Wingate*2022 · 157 citations*](https://md.research.elamur.ai/free/en/papers/robinson-2022-leveraging-large-language-models-multiple/) **[Do LLMs Exhibit Human-like Response Biases? A Case Study in Survey Design](https://md.research.elamur.ai/free/en/papers/tjuatja-2024-do-llms-exhibit-human-like/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Lindia Tjuatja, Valerie Chen, Tongshuang Wu, et al.*2024 · 136 citations* [**A Roadmap to Pluralistic Alignment arXiv:2402.05070**Taylor Sorensen, Jared Moore, Jillian Fisher, et al.*2024 · 135 citations*](https://md.research.elamur.ai/free/en/papers/sorensen-2024-roadmap-pluralistic-alignment/) [**Artificial Artificial Artificial Intelligence: Crowd Workers Widely Use Large Language Models for Text Production Tasks arXiv:2306.07899**Veniamin Veselovsky, Manoel Horta Ribeiro, Robert West*2023 · 127 citations*](https://md.research.elamur.ai/free/en/papers/veselovsky-2023-artificial-artificial-artificial-intelligence-crowd/) **[Quantifying the Persona Effect in LLM Simulations](https://md.research.elamur.ai/free/en/papers/hu-2024-quantifying-persona-effect-llm-simulations/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Tiancheng Hu, Nigel Collier*2024 · 116 citations* **[Culturally Aware and Adapted NLP: A Taxonomy and a Survey of the State of the Art](https://md.research.elamur.ai/free/en/papers/liu-2025-culturally-aware-adapted-nlp-taxonomy/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Chen Cecilia Liu, Iryna Gurevych, Anna Korhonen*2025 · 89 citations* **[Mitigating Label Biases for In-context Learning](https://md.research.elamur.ai/free/en/papers/fei-2023-mitigating-label-biases-context-learning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yu Fei, Yifan Hou, Zeming Chen, et al.*2023 · 79 citations* **[Sensitivity, Performance, Robustness: Deconstructing the Effect of Sociodemographic Prompting](https://md.research.elamur.ai/free/en/papers/beck-2024-sensitivity-performance-robustness-deconstructing-effect/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Tilman Beck, Hendrik Schuff, Anne Lauscher, et al.*2024 · 68 citations* **[Pragmatics in the Era of Large Language Models: A Survey on Datasets, Evaluation, Opportunities and Challenges](https://md.research.elamur.ai/free/en/papers/ma-2025-pragmatics-era-large-language-models/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Bolei Ma, Yuting Li, Wei Zhou, et al.*2025 · 49 citations* **[German General Social Survey Personas: A Survey-Derived Persona Prompt Collection for Population-Aligned LLM Studies](https://md.research.elamur.ai/free/en/papers/rupprecht-2026-german-general-social-survey-personas/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Jens Rupprecht, Leon Froehling, Claudia Wagner, et al.*2026 · 1 citation* **[R.U.Psycho? A Framework for Robust Unified Psychometric Testing of Language Models](https://md.research.elamur.ai/free/en/papers/schelb-2026-r-u-psycho-framework-robust/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Julian Schelb, Orr Borin, David Garcia, et al.*2026* 256 more citing papers of our library have no page here yet. - [← back to](https://md.research.elamur.ai/free/en/authors/nancy-fulda/) — Nancy Fulda