AnnoLLM: Making large language models to be better crowdsourced annotators

Xingwei He; Zhenghao Lin; Yeyun Gong; A-Long Jin; Hang Zhang; Chen Lin; Jian Jiao; Siu-Ming Yiu; Nan Duan; Weizhu Chen

AnnoLLM: Making large language models to be better crowdsourced annotators

Xingwei He, Zhenghao Lin, Yeyun Gong, A-Long Jin, Hang Zhang, Chen Lin, Jian Jiao, Siu-Ming Yiu, Nan Duan, Weizhu Chen

Department of Communications and Networking

Research output: Chapter in Book or Report/Conference proceeding › Conference Proceeding › peer-review

Original language	English
Title of host publication	The North American Chapter of the Association for Computational Linguistics
Publication status	Published - 2024

Cite this

@inproceedings{f5710b0ab0b7446c98b5b4213ae8755b,

title = "AnnoLLM: Making large language models to be better crowdsourced annotators",

author = "Xingwei He and Zhenghao Lin and Yeyun Gong and A-Long Jin and Hang Zhang and Chen Lin and Jian Jiao and Siu-Ming Yiu and Nan Duan and Weizhu Chen",

year = "2024",

language = "English",

booktitle = "The North American Chapter of the Association for Computational Linguistics",

}

TY - GEN

T1 - AnnoLLM: Making large language models to be better crowdsourced annotators

AU - He, Xingwei

AU - Lin, Zhenghao

AU - Gong, Yeyun

AU - Jin, A-Long

AU - Zhang, Hang

AU - Lin, Chen

AU - Jiao, Jian

AU - Yiu, Siu-Ming

AU - Duan, Nan

AU - Chen, Weizhu

PY - 2024

Y1 - 2024

M3 - Conference Proceeding

BT - The North American Chapter of the Association for Computational Linguistics

ER -