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The traditional data annotation process is often labor-intensive, time-consuming, and susceptible to human bias, which complicates the management of increasingly complex datasets.
“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., · 1901
Earlier work this paper cites.
“Recursive deep models for semantic compositionality over a sentiment treebank,”
Richard Socher, Alex Perelygin, Jean Wu, Jason Chuang, Christopher D. Manning, A. Ng, and Christopher Potts, · 2013
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“Character-level convolutional networks for text classification,”
Xiang Zhang, Junbo Zhao, and Yann LeCun, · 2015
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“Dbpedia - a large-scale, multilingual knowledge base extracted from wikipedia,”
Jens Lehmann, Robert Isele, Max Jakob, Anja Jentzsch, Dimitris Kontokostas, Pablo N. Mendes, Sebastian Hellmann, Mohamed Morsey, Patrick van Kleef, S. Auer, and Christian Bizer, · 2015
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“Survey of data annotation,”
Li CAI, Shu-Ting WANG, Jun-Hui LIU, and Yang-Yong ZHU, · 2019
Earlier work this paper cites.
“Is gpt-3 a good data annotator?,”
Bosheng Ding, Chengwei Qin, Linlin Liu, Lidong Bing, Shafiq Joty, and Boyang Li, · 2022
Earlier work this paper cites.
“Finetuned language models are zero-shot learners,”
Jason Wei, Maarten Bosma, Vincent Zhao, Kelvin Guu, Adams Wei Yu, Brian Lester, Nan Du, Andrew M. Dai, and Quoc V. Le, · 2022
Earlier work this paper cites.
“Improving in-context few-shot learning via self-supervised training,”
Mingda Chen, Jingfei Du, Ramakanth Pasunuru, Todor Mihaylov, Srini Iyer, Ves Stoyanov, and Zornitsa Kozareva, · 2022
Earlier work this paper cites.
“Chain-of-thought prompting elicits reasoning in large language models,”
Jason Wei, Xuezhi Wang, Dale Schuurmans, Maarten Bosma, Fei Xia, Ed Chi, Quoc V Le, Denny Zhou, et al., · 2022
Cited alongside, same era.
“Automated annotation with generative ai requires validation,”
Nicholas Pangakis, Samuel Wolken, and Neil Fasching, · 2023
Cited alongside, same era.
“Chatgpt outperforms crowd workers for text-annotation tasks,”
Fabrizio Gilardi, Meysam Alizadeh, and Maël Kubli, · 2023
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“Testing the reliability of chatgpt for text annotation and classification: A cautionary remark,”
Michael V. Reiss, · 2023
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“Siren’s song in the ai ocean: A survey on hallucination in large language models,”
Yue Zhang, Yafu Li, Leyang Cui, Deng Cai, et al., · 2023
“Agentverse: Facilitating multi-agent collaboration and exploring emergent behaviors,”
Weize Chen, Yusheng Su, Jingwei Zuo, Cheng Yang, Chenfei Yuan, Chi-Min Chan, Heyang Yu, Yaxi Lu, Yi-Hsin Hung, Chen Qian, et al., · 2023
Later among the works it cites.
“Large language models for data annotation: A survey,”
Zhen Tan, Alimohammad Beigi, Song Wang, Ruocheng Guo, Amrita Bhattacharjee, Bohan Jiang, Mansooreh Karami, Jundong Li, Lu Cheng, and Huan Liu, · 2024
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“A comparative study on annotation quality of crowdsourcing and llm via label aggregation,”
Jiyi Li, · 2024
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“Brainstorming brings power to large language models of knowledge reasoning,”
Zining Qin, Chenhao Wang, Huiling Qin, and Weijia Jia, · 2024
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“Universal self-consistency for large language models,”
Xinyun Chen, Renat Aksitov, Uri Alon, Jie Ren, Kefan Xiao, Pengcheng Yin, Sushant Prakash, Charles Sutton, Xuezhi Wang, and Denny Zhou, · 2024
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Cited alongside, same era.
Israt Jahan, Md Tahmid Rahman Laskar, Chun Peng, and J. Huang, · 2023
Cited alongside, same era.
“# instag: Instruction tagging for analyzing supervised fine-tuning of large language models,”
Keming Lu, Hongyi Yuan, Zheng Yuan, Runji Lin, Junyang Lin, Chuanqi Tan, Chang Zhou, and Jingren Zhou, · 2023
Cited alongside, same era.
“Can large language models be an alternative to human evaluations?,”
Cheng-Han Chiang and Hung yi Lee, · 2023
Cited alongside, same era.
“Pdfchatannotator: A human-llm collaborative multi-modal data annotation tool for pdf-format catalogs,”
Yi Tang, Chia-Ming Chang, and Xi Yang, · 2024
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“Character attribute extraction from movie scripts using llms,”
Sabyasachee Baruah and Shrikanth Narayanan, · 2024
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