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Data annotation refers to the labeling or tagging of textual data with relevant information.
Pubmedqa: A dataset for biomedical research question answering
Qiao Jin, Bhuwan Dhingra, Zhengping Liu, William Cohen, and Xinghua Lu. 2019 · 2019
Earlier work this paper cites.
Measuring massive multitask language understanding
Dan Hendrycks, Collin Burns, Steven Basart, Andy Zou, Mantas Mazeika, Dawn Song, and Jacob Steinhardt. 2020 · 2020
Earlier work this paper cites.
Coda-19: Using a non-expert crowd to annotate research aspects on 10,000+ abstracts in the covid-19 open research dataset
Ting-Hao Kenneth Huang, Chieh-Yang Huang, Chien-Kuang Cornelia Ding, Yen-Chia Hsu, and C Lee Giles. 2020 · 2020
Earlier work this paper cites.
Cord-19: The covid-19 open research dataset
Lucy Lu Wang, Kyle Lo, Yoganand Chandrasekhar, Russell Reas, Jiangjiang Yang, Douglas Burdick, Darrin Eide, Kathryn Funk, Yannis Katsis, Rodney Kinney, et al. 2020 · 2020
Earlier work this paper cites.
Evaluating large language models trained on code
Mark Chen, Jerry Tworek, Heewoo Jun, Qiming Yuan, Henrique Ponde de Oliveira Pinto, Jared Kaplan, Harri Edwards, Yuri Burda, Nicholas Joseph, Greg Brockman, et al. 2021 · 2021
Earlier work this paper cites.
Chatgpt goes to law school
Jonathan H Choi, Kristin E Hickman, Amy B Monahan, and Daniel Schwarcz. 2021 · 2021
Earlier work this paper cites.
Cuad: An expert-annotated nlp dataset for legal contract review
Dan Hendrycks, Collin Burns, Anya Chen, and Spencer Ball. 2021 · 2021
Earlier work this paper cites.
Hierarchical annotation for building a suite of clinical natural language processing tasks: Progress note understanding
Yanjun Gao, Dmitriy Dligach, Timothy Miller, Samuel Tesch, Ryan Laffin, Matthew M Churpek, and Majid Afshar. 2022 · 2022
Earlier work this paper cites.
Large language models are zero-shot reasoners
Takeshi Kojima, Shixiang Shane Gu, Machel Reid, Yutaka Matsuo, and Yusuke Iwasawa. 2022 · 2022
Earlier work this paper cites.
Self-consistency improves chain of thought reasoning in language models
Xuezhi Wang, Jason Wei, Dale Schuurmans, Quoc V Le, Ed H Chi, Sharan Narang, Aakanksha Chowdhery, and Denny Zhou. 2022 · 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 · 2022
Earlier work this paper cites.
Josh Achiam, Steven Adler, Sandhini Agarwal, Lama Ahmad, Ilge Akkaya, Florencia Leoni Aleman, Diogo Almeida, Janko Altenschmidt, Sam Altman, Shyamal Anadkat, et al. 2023 · 2023
Earlier work this paper cites.
Meysam Alizadeh, Maël Kubli, Zeynab Samei, Shirin Dehghani, Juan Diego Bermeo, Maria Korobeynikova, and Fabrizio Gilardi. 2023 · 2023
Cited alongside, same era.
Large language models as annotators: Enhancing generalization of nlp models at minimal cost
Parikshit Bansal and Amit Sharma. 2023 · 2023
Cited alongside, same era.
Can gpt models be financial analysts? an evaluation of chatgpt and gpt-4 on mock cfa exams
Ethan Callanan, Amarachi Mbakwe, Antony Papadimitriou, Yulong Pei, Mathieu Sibue, Xiaodan Zhu, Zhiqiang Ma, Xiaomo Liu, and Sameena Shah. 2023 · 2023
Cited alongside, same era.
Reconcile: Round-table conference improves reasoning via consensus among diverse llms
Justin Chih-Yao Chen, Swarnadeep Saha, and Mohit Bansal. 2023 · 2023
Cited alongside, same era.
Llmaaa: Making large language models as active annotators
Ruoyu Zhang, Yanzeng Li, Yongliang Ma, Ming Zhou, and Lei Zou. 2023 · 2023
Later among the works it cites.
Can chatgpt reproduce human-generated labels? a study of social computing tasks
Yiming Zhu, Peixian Zhang, Ehsan-Ul Haq, Pan Hui, and Gareth Tyson. 2023 · 2023
Later among the works it cites.
The claude 3 model family: Opus, sonnet, haiku
AI Anthropic. 2024 · 2024
Closest in time.
Gpts are multilingual annotators for sequence generation tasks
Juhwan Choi, Eunju Lee, Kyohoon Jin, and YoungBin Kim. 2024 · 2024
Closest in time.
Legalbench: A collaboratively built benchmark for measuring legal reasoning in large language models
Neel Guha, Julian Nyarko, Daniel Ho, Christopher Ré, Adam Chilton, Alex Chohlas-Wood, Austin Peters, Brandon Waldon, Daniel Rockmore, Diego Zambrano, et al. 2024 · 2024
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Is gpt-3 a good data annotator?
Bosheng Ding, Chengwei Qin, Linlin Liu, Yew Ken Chia, Boyang Li, Shafiq Joty, and Lidong Bing. 2023 · 2023
Cited alongside, same era.
Improving factuality and reasoning in language models through multiagent debate
Yilun Du, Shuang Li, Antonio Torralba, Joshua B Tenenbaum, and Igor Mordatch. 2023 · 2023
Cited alongside, same era.
Chatgpt outperforms crowd workers for text-annotation tasks
Fabrizio Gilardi, Meysam Alizadeh, and Maël Kubli. 2023 · 2023
Cited alongside, same era.
Annollm: Making large language models to be better crowdsourced annotators
Xingwei He, Zhenghao Lin, Yeyun Gong, Alex Jin, Hang Zhang, Chen Lin, Jian Jiao, Siu Ming Yiu, Nan Duan, Weizhu Chen, et al. 2023 · 2023
Cited alongside, same era.
Refind: Relation extraction financial dataset
Simerjot Kaur, Charese Smiley, Akshat Gupta, Joy Sain, Dongsheng Wang, Suchetha Siddagangappa, Toyin Aguda, and Sameena Shah. 2023 · 2023
Cited alongside, same era.
Gpt-3.5 turbo
OpenAI. 2023 · 2023
Cited alongside, same era.
Gpqa: A graduate-level google-proof q&a benchmark
David Rein, Betty Li Hou, Asa Cooper Stickland, Jackson Petty, Richard Yuanzhe Pang, Julien Dirani, Julian Michael, and Samuel R Bowman. 2023 · 2023
Cited alongside, same era.
Trillion dollar words: A new financial dataset, task & market analysis
Agam Shah, Suvan Paturi, and Sudheer Chava. 2023 · 2023
Cited alongside, same era.
Closest in time.
Gpt-4 passes the bar exam
Daniel Martin Katz, Michael James Bommarito, Shang Gao, and Pablo Arredondo. 2024 · 2024
Closest in time.
Self-refine: Iterative refinement with self-feedback
Aman Madaan, Niket Tandon, Prakhar Gupta, Skyler Hallinan, Luyu Gao, Sarah Wiegreffe, Uri Alon, Nouha Dziri, Shrimai Prabhumoye, Yiming Yang, et al. 2024 · 2024
Closest in time.
Hello gpt4-o
OpenAI. 2024 · 2024
Closest in time.
Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context
Machel Reid, Nikolay Savinov, Denis Teplyashin, Dmitry Lepikhin, Timothy Lillicrap, Jean-baptiste Alayrac, Radu Soricut, Angeliki Lazaridou, Orhan Firat, Julian Schrittwieser, et al. 2024 · 2024
Closest in time.
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 · 2024
Closest in time.
Two tales of persona in llms: A survey of role-playing and personalization
Yu-Min Tseng, Yu-Chao Huang, Teng-Yun Hsiao, Yu-Ching Hsu, Jia-Yin Foo, Chao-Wei Huang, and Yun-Nung Chen. 2024 · 2024
Closest in time.
Rethinking the bounds of llm reasoning: Are multi-agent discussions the key?
Qineng Wang, Zihao Wang, Ying Su, Hanghang Tong, and Yangqiu Song. 2024 · 2024
Closest in time.