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In-context Learning (ICL) is one of the key methods for enhancing the performance of large language models on specific tasks by providing a set of few-shot examples.
Toward semantics-based answer pinpointing
Eduard Hovy, Laurie Gerber, Ulf Hermjakob, et al · 2001
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Learning question classifiers
Xin Li and Dan Roth · 2002
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A sentimental education: Sentiment analysis using subjectivity summarization based on minimum cuts
Bo Pang and Lillian Lee · 2004
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The pascal recognising textual entailment challenge
Ido Dagan, Oren Glickman, and Bernardo Magnini · 2005
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Recursive deep models for semantic compositionality over a sentiment treebank
Richard Socher, Alex Perelygin, Jean Wu, et al · 2013
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Character-level convolutional networks for text classification
Xiang Zhang, Junbo Zhao, and Yann LeCun · 2015
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SQuAD: 100,000+ questions for machine comprehension of text
Pranav Rajpurkar, Jian Zhang, Konstantin Lopyrev, et al · 2016
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Hate Speech Dataset from a White Supremacy Forum
Ona de Gibert, Naiara Perez, Aitor García-Pablos, et al · 2018
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Language models are few-shot learners
Tom Brown, Benjamin Mann, Nick Ryder, et al · 2020
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Ethos: an online hate speech detection dataset, 2020
Ioannis Mollas, Zoe Chrysopoulou, Stamatis Karlos, et al · 2020
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Mpnet: Masked and permuted pre-training for language understanding
Kaitao Song, Xu Tan, Tao Qin, et al · 2020
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Calibrate before use: Improving few-shot performance of language models
Zihao Zhao, Eric Wallace, Shi Feng, et al · 2021
Cited alongside, same era.
Data distributional properties drive emergent in-context learning in transformers
Stephanie Chan, Adam Santoro, Andrew Lampinen, et al · 2022
Cited alongside, same era.
What can transformers learn in-context? a case study of simple function classes
Shivam Garg, Dimitris Tsipras, Percy S Liang, et al · 2022
Cited alongside, same era.
What makes good in-context examples for GPT-3?
Jiachang Liu, Dinghan Shen, Yizhe Zhang, et al · 2022
Cited alongside, same era.
Fantastically ordered prompts and where to find them: Overcoming few-shot prompt order sensitivity
Yao Lu, Max Bartolo, Alastair Moore, et al · 2022
Cited alongside, same era.
A survey on in-context learning
Qingxiu Dong, Lei Li, Damai Dai, et al · 2023
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Finding support examples for in-context learning
Xiaonan Li and Xipeng Qiu · 2023
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Towards informative few-shot prompt with maximum information gain for in-context learning
Hongfu Liu and Ye Wang · 2023
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In-context learning for text classification with many labels
Aristides Milios, Siva Reddy, and Dzmitry Bahdanau · 2023
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In-context unlearning: Language models as few shot unlearners
Martin Pawelczyk, Seth Neel, and Himabindu Lakkaraju · 2023
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Sewon Min, Xinxi Lyu, Ari Holtzman, et al · 2022
Cited alongside, same era.
Learning to retrieve prompts for in-context learning
Ohad Rubin, Jonathan Herzig, and Jonathan Berant · 2022
Cited alongside, same era.
Selective annotation makes language models better few-shot learners
Hongjin Su, Jungo Kasai, Chen Henry Wu, et al · 2022
Cited alongside, same era.
An explanation of in-context learning as implicit bayesian inference
Sang Michael Xie, Aditi Raghunathan, Percy Liang, et al · 2022
Cited alongside, same era.
Ground-truth labels matter: A deeper look into input-label demonstrations
Kang Min Yoo, Junyeob Kim, Hyuhng Joon Kim, et al · 2022
Cited alongside, same era.
Active example selection for in-context learning
Yiming Zhang, Shi Feng, and Chenhao Tan · 2022
Cited alongside, same era.
Chengwei Qin, Aston Zhang, Anirudh Dagar, et al · 2023
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Llama 2: Open foundation and fine-tuned chat models
Hugo Touvron, Louis Martin, Kevin Stone, et al · 2023
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Larger language models do in-context learning differently
Jerry Wei, Jason Wei, Yi Tay, et al · 2023
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Self-adaptive in-context learning: An information compression perspective for in-context example selection and ordering
Zhiyong Wu, Yaoxiang Wang, Jiacheng Ye, et al · 2023
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Baichuan 2: Open large-scale language models
Aiyuan Yang, Bin Xiao, Bingning Wang, et al · 2023
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Automatic chain of thought prompting in large language models
Zhuosheng Zhang, Aston Zhang, Mu Li, et al · 2023
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