Fetching the paper…
Reading the bibliography…
Prompting LLMs offers an efficient way to guide output generation without explicit model training.
Bleu: a method for automatic evaluation of machine translation
Kishore Papineni, Salim Roukos, Todd Ward, and Wei-Jing Zhu · 2002
Earlier work this paper cites.
Rouge: A package for automatic evaluation of summaries
Chin-Yew Lin · 2004
Earlier work this paper cites.
Language models are few-shot learners
Tom Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared D Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, et al · 2020
Earlier work this paper cites.
A survey on in-context learning
Qingxiu Dong, Lei Li, Damai Dai, Ce Zheng, Jingyuan Ma, Rui Li, Heming Xia, Jingjing Xu, Zhiyong Wu, Tianyu Liu, et al · 2022
Earlier work this paper cites.
Emergent abilities of large language models
Jason Wei, Yi Tay, Rishi Bommasani, Colin Raffel, Barret Zoph, Sebastian Borgeaud, Dani Yogatama, Maarten Bosma, Denny Zhou, Donald Metzler, et al · 2022
Earlier work this paper cites.
Query understanding in the age of large language models
Avishek Anand, Abhijit Anand, Vinay Setty, et al · 2023
Earlier work this paper cites.
Jiho Shin, Clark Tang, Tahmineh Mohati, Maleknaz Nayebi, Song Wang, and Hadi Hemmati · 2023
Earlier work this paper cites.
This prompt is measuring¡ mask¿: evaluating bias evaluation in language models
Seraphina Goldfarb-Tarrant, Eddie Ungless, Esma Balkir, and Su Lin Blodgett · 2023
Cited alongside, same era.
The mystery of in-context learning: A comprehensive survey on interpretation and analysis
Yuxiang Zhou, Jiazheng Li, Yanzheng Xiang, Hanqi Yan, Lin Gui, and Yulan He · 2023
Cited alongside, same era.
Xinyi Wang, Wanrong Zhu, and William Yang Wang · 2023
Cited alongside, same era.
Learning to retrieve in-context examples for large language models
L. Wang, N. Yang, and F. Wei · 2023
Cited alongside, same era.
Larger language models do in-context learning differently
J. Wei, Y. Tay, D. Tran, A. Webson, Y. Lu, X. Chen, H. Liu, D. Huang, D. Zhou, and T. Ma · 2023
Sequential llm framework for fashion recommendation
Han Liu, Xianfeng Tang, Tianlang Chen, Jiapeng Liu, Indu Indu, Henry Peng Zou, Peng Dai, Roberto Fernandez Galan, Michael D Porter, Dongmei Jia, et al · 2024
Later among the works it cites.
Long-context llms struggle with long in-context learning
Tianle Li, Ge Zhang, Quy Duc Do, Xiang Yue, and Wenhu Chen · 2024
Later among the works it cites.
Prewrite: Prompt rewriting with reinforcement learning
Weize Kong, Spurthi Amba Hombaiah, Mingyang Zhang, Qiaozhu Mei, and Michael Bendersky · 2024
Later among the works it cites.
Ziyang Xu, Keqin Peng, Liang Ding, Dacheng Tao, and Xiliang Lu · 2024
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Cited alongside, same era.
Albert Q Jiang, A Sablayrolles, A Mensch, C Bamford, D Singh Chaplot, Ddl Casas, F Bressand, G Lengyel, G Lample, L Saulnier, et al · 2023
Cited alongside, same era.
Efficient memory management for large language model serving with pagedattention
Woosuk Kwon, Zhuohan Li, Siyuan Zhuang, Ying Sheng, Lianmin Zheng, Cody Hao Yu, Joseph E. Gonzalez, Hao Zhang, and Ion Stoica · 2023
Cited alongside, same era.
Zhuowei Li, Zihao Xu, Ligong Han, Yunhe Gao, Song Wen, Di Liu, Hao Wang, and Dimitris N Metaxas · 2024
Later among the works it cites.
Llm-friendly knowledge representation for customer support
Hanchen Su, Wei Luo, Yashar Mehdad, Wei Han, Elaine Liu, Wayne Zhang, Mia Zhao, and Joy Zhang · 2025
Closest in time.
Effects of prompt length on domain-specific tasks for large language models
Qibang Liu, Wenzhe Wang, and Jeffrey Willard · 2025
Closest in time.