--- title: "Who cites Andy Rosenbaum — 105 papers of our library" description: "105 papers of the Elamur Research library cite the works of Andy Rosenbaum, found in their bibliographies; the most cited first." canonical: "https://research.elamur.ai/free/en/authors/andy-rosenbaum/cited-by/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/andy-rosenbaum/cited-by/) [home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / [Andy Rosenbaum](https://md.research.elamur.ai/free/en/authors/andy-rosenbaum/) / cited by # Who cites Andy Rosenbaum 109 citations of their works from 105 papers of our library (of the 141,840 whose bibliographies we read) · 18 with a page here, the most cited first · [← Andy Rosenbaum](https://md.research.elamur.ai/free/en/authors/andy-rosenbaum/) 1. **[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 · 2,863 citations* 2. **[A Comprehensive Overview of Large Language Models](https://md.research.elamur.ai/free/en/papers/naveed-2023-comprehensive-overview-large-language-models/) [ACM Transactions on Intelligent Systems and Technology](https://md.research.elamur.ai/free/en/venues/acm-transactions-on-intelligent-systems-and-technology/)**Humza Naveed, Asad Ullah Khan, Shi Qiu, et al.*2023 · 1,286 citations* 3. [**Harnessing the Power of LLMs in Practice: A Survey on ChatGPT and Beyond arXiv:2304.13712**Jingfeng Yang, Hongye Jin, Ruixiang Tang, et al.*2023 · 811 citations*](https://md.research.elamur.ai/free/en/papers/yang-2023-harnessing-power-llms-practice-survey/) 4. [**Crosslingual Generalization through Multitask Finetuning arXiv:2211.01786**Niklas Muennighoff, Thomas Wang, Lintang Sutawika, et al.*2022 · 695 citations*](https://md.research.elamur.ai/free/en/papers/muennighoff-2022-crosslingual-generalization-through-multitask-finetuning/) 5. **[CAMEL: Communicative Agents for "Mind" Exploration of Large Language Model Society](https://md.research.elamur.ai/free/en/papers/li-2023-camel-communicative-agents-mind/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Guohao Li, Hasan Abed Al Kader Hammoud, Hani Itani, et al.*2023 · 692 citations* 6. [**BloombergGPT: A Large Language Model for Finance arXiv:2303.17564**Shijie Wu, Ozan Irsoy, Steven Lu, et al.*2023 · 612 citations*](https://md.research.elamur.ai/free/en/papers/wu-2023-bloomberggpt-large-language-model-finance/) 7. **[Instruction Tuning for Large Language Models: A Survey](https://md.research.elamur.ai/free/en/papers/zhang-2023-instruction-tuning-large-language-models/) [ACM Computing Surveys](https://md.research.elamur.ai/free/en/venues/acm-computing-surveys/)**Shengyu Zhang, Linfeng Dong, Xiaoya Li, et al.*2023 · 517 citations* 8. [**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/) 9. **[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 · 259 citations* 10. **[In-context Examples Selection for Machine Translation](https://md.research.elamur.ai/free/en/papers/agrawal-2023-context-examples-selection-machine-translation/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Sweta Agrawal, Chunting Zhou, Mike Lewis, et al.*2023 · 242 citations* 11. **[SODA: Million-scale Dialogue Distillation with Social Commonsense Contextualization](https://md.research.elamur.ai/free/en/papers/kim-2023-soda-million-scale-dialogue-distillation/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Hyunwoo Kim, Jack Hessel, Liwei Jiang, et al.*2023 · 201 citations* 12. **[MathDial: A Dialogue Tutoring Dataset with Rich Pedagogical Properties Grounded in Math Reasoning Problems](https://md.research.elamur.ai/free/en/papers/macina-2023-mathdial-dialogue-tutoring-dataset-rich/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jakub Macina, Nico Daheim, Sankalan Chowdhury, et al.*2023 · 130 citations* 13. **[Prompting and Evaluating Large Language Models for Proactive Dialogues: Clarification, Target-guided, and Non-collaboration](https://md.research.elamur.ai/free/en/papers/deng-2023-prompting-evaluating-large-language-models/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yang Deng, Lizi Liao, Liang Chen, et al.*2023 · 128 citations* 14. [**Knowledge-Augmented Language Model Prompting for Zero-Shot Knowledge Graph Question Answering arXiv:2306.04136**Jinheon Baek, Alham Fikri Aji, Amir Saffari*2023 · 119 citations*](https://md.research.elamur.ai/free/en/papers/baek-2023-knowledge-augmented-language-model-prompting/) 15. [**ALLaM: Large Language Models for Arabic and English arXiv:2407.15390**M Saiful Bari, Yazeed Alnumay, Norah A. Alzahrani, et al.*2024 · 113 citations*](https://md.research.elamur.ai/free/en/papers/bari-2024-allam-large-language-models-arabic/) 16. [**Investigating the Translation Performance of a Large Multilingual Language Model: the Case of BLOOM arXiv:2303.01911**Rachel Bawden, François Yvon*2023 · 85 citations*](https://md.research.elamur.ai/free/en/papers/bawden-2023-investigating-translation-performance-large-multilingual/) 17. **[E-CONAN (Entailment, CONtradition And Neutral) Benchmarks: Arabic Textual Entailment and Natural Inference Datasets](https://md.research.elamur.ai/free/en/papers/jallad-2026-e-conan-entailment-contradition-neutral-benchmarks/) [IEEE Access](https://md.research.elamur.ai/free/en/venues/ieee-access/)**Khloud AL Jallad, Nada Ghneim, Ghaida Rebdawi*2026* 18. [**E-CONAN (Entailment, CONtradition And Neutral) Diagnostics Dataset Investigating Linguistic Phenomena in Arabic Natural Language Understanding arXiv:2609.33530**Khloud AL Jallad, Nada Ghneim, Ghaida Rebdawi*2026*](https://md.research.elamur.ai/free/en/papers/jallad-2026-e-conan-entailment-contradition-neutral/) 87 more citing papers of our library have no page here yet. - [← back to](https://md.research.elamur.ai/free/en/authors/andy-rosenbaum/) — Andy Rosenbaum