--- title: "Who cites Large Language Models Are — 85 citing papers" description: "85 papers of the Elamur Research library cite «Large Language Models Are Latent Variable Models: Explaining and Finding Good…" canonical: "https://research.elamur.ai/free/en/papers/wang-2023-large-language-models-latent-variable/cited-by/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/wang-2023-large-language-models-latent-variable/cited-by/) [home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [Large Language Models Are Latent Variable Models…](https://md.research.elamur.ai/free/en/papers/wang-2023-large-language-models-latent-variable/) / cited by # Who cites «Large Language Models Are Latent Variable Models: Explaining and Finding Good Demonstrations for In-Context Learning» 85 papers of our library cite it (of the 149,439 whose bibliographies we read) · 13 with a page here, the most cited first · [← back to «Large Language Models Are Latent Variable Models: Explaining and Finding Good Demonstrations for In-Context Learning»](https://md.research.elamur.ai/free/en/papers/wang-2023-large-language-models-latent-variable/) 1. [**A Survey on In-context Learning arXiv:2301.00234**Qingxiu Dong, Lei Li, Damai Dai, et al.*2023 · 978 citations*](https://md.research.elamur.ai/free/en/papers/dong-2023-survey-context-learning/) 2. [**LegalBench: A Collaboratively Built Benchmark for Measuring Legal Reasoning in Large Language Models arXiv:2308.11462**Neel Guha; Julian Nyarko; Daniel E. Ho; Christopher Re; Adam Chilton; Aditya Narayana; Alex Chohlas-Wood; Austin Peters; Brandon Waldon; Daniel N. Rockmore; Diego Zambrano; Dmitry Talisman; Enam Hoque; Faiz Surani; Frank Fagan; Galit Sarfaty; Gregory M. Dickinson; Haggai Porat; Jason Hegland; Jessica Wu; Joe Nudell; Joel Niklaus; John Nay; Jonathan H. Choi; Kevin Tobia; Margaret Hagan; Megan Ma; Michael Livermore; Nikon Rasumov-Rahe; Nils Holzenberger; Noam Kolt; Peter Henderson; Sean Rehaag; Sharad Goel; Shang Gao; Spencer Williams; Sunny Gandhi; Tom Zur; Varun Iyer;, Zehua Li*2023 · 389 citations*](https://md.research.elamur.ai/free/en/papers/guha-2023-legalbench-collaboratively-built-benchmark-measuring/) 3. **[A Survey on Model Compression for Large Language Models](https://md.research.elamur.ai/free/en/papers/zhu-2024-survey-model-compression-large-language/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Xunyu Zhu, Jian Li, Yong Liu, et al.*2024 · 381 citations* 4. [**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/) 5. [**LESS: Selecting Influential Data for Targeted Instruction Tuning arXiv:2402.04333**Mengzhou Xia, Sadhika Malladi, Suchin Gururangan, et al.*2024 · 178 citations*](https://md.research.elamur.ai/free/en/papers/xia-2024-less-selecting-influential-data-targeted/) 6. **[Many-Shot In-Context Learning](https://md.research.elamur.ai/free/en/papers/agarwal-2024-many-shot-context-learning/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Rishabh Agarwal, Avi Singh, Lei M. Zhang, et al.*2024 · 142 citations* 7. [**A Survey on Data Selection for Language Models arXiv:2402.16827**Alon Albalak, Yanai Elazar, Sang Michael Xie, et al.*2024 · 95 citations*](https://md.research.elamur.ai/free/en/papers/albalak-2024-survey-data-selection-language-models/) 8. **[Testing the General Deductive Reasoning Capacity of Large Language Models Using OOD Examples](https://md.research.elamur.ai/free/en/papers/saparov-2023-testing-general-deductive-reasoning-capacity/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Abulhair Saparov, Richard Yuanzhe Pang, Vishakh Padmakumar, et al.*2023 · 84 citations* 9. **[Large Language Model Instruction Following: A Survey of Progresses and Challenges](https://md.research.elamur.ai/free/en/papers/lou-2024-large-language-model-instruction-following/) [Computational Linguistics](https://md.research.elamur.ai/free/en/venues/cl/)**Renze Lou, Kai Zhang, Wenpeng Yin*2024 · 83 citations* 10. [**In-context Learning with Retrieved Demonstrations for Language Models: A Survey arXiv:2401.11624**Man Luo, Xin Xu, Yue Liu, et al.*2024 · 54 citations*](https://md.research.elamur.ai/free/en/papers/luo-2024-context-learning-retrieved-demonstrations-language/) 11. [**Understanding Emergent In-Context Learning from a Kernel Regression Perspective arXiv:2305.12766**Chi Han, Ziqi Wang, Han Zhao, et al.*2023 · 21 citations*](https://md.research.elamur.ai/free/en/papers/han-2023-understanding-emergent-context-learning-kernel/) 12. **[Subjectivity Detection in English News using Large Language Models](https://md.research.elamur.ai/free/en/papers/shokri-2024-subjectivity-detection-english-news-large/) [Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis](https://md.research.elamur.ai/free/en/venues/wassa/)**Mohammad Shokri, Vivek Sharma, Elena Filatova, et al.*2024 · 7 citations* 13. [**Towards Controllable Natural Language Inference through Lexical Inference Types arXiv:2308.03581**Yingji Zhang, Danilo S. Carvalho, Ian Pratt-Hartmann, et al.*2023 · 2 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2023-towards-controllable-natural-language-inference/) 72 more papers of our library cite it; they have no page here yet. - [← back to](https://md.research.elamur.ai/free/en/papers/wang-2023-large-language-models-latent-variable/) — Large Language Models Are Latent Variable Models: Explaining and Finding Good Demonstrations for In-Context Learning