Learning in the Wild: Towards Leveraging Unlabeled Data for Effectively Tuning Pre-trained Code Models. Gao, S., Mao, W., Gao, C., Li, L., Hu, X., Xia, X., & Lyu, M. R. In ICSE, pages 80:1-80:13, 2024. ACM.
Learning in the Wild: Towards Leveraging Unlabeled Data for Effectively Tuning Pre-trained Code Models. [link]Link  Learning in the Wild: Towards Leveraging Unlabeled Data for Effectively Tuning Pre-trained Code Models. [link]Paper  bibtex   
@inproceedings{conf/icse/GaoMG000L24,
  added-at = {2024-05-31T00:00:00.000+0200},
  author = {Gao, Shuzheng and Mao, Wenxin and Gao, Cuiyun and Li, Li and Hu, Xing and Xia, Xin and Lyu, Michael R.},
  biburl = {https://www.bibsonomy.org/bibtex/2971534d2475b01c95402373c4bc94034/dblp},
  booktitle = {ICSE},
  crossref = {conf/icse/2024},
  ee = {https://doi.org/10.1145/3597503.3639216},
  interhash = {860d77fa5bdbf8751c68654b52e90ed3},
  intrahash = {971534d2475b01c95402373c4bc94034},
  keywords = {dblp},
  pages = {80:1-80:13},
  publisher = {ACM},
  timestamp = {2024-06-03T07:20:02.000+0200},
  title = {Learning in the Wild: Towards Leveraging Unlabeled Data for Effectively Tuning Pre-trained Code Models.},
  url = {http://dblp.uni-trier.de/db/conf/icse/icse2024.html#GaoMG000L24},
  year = 2024
}

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