Learning in the Wild: Towards Leveraging Unlabeled Data for Effectively Tuning Pre-trained Code Models

Research article (Proceedings of the IEEE/ACM 46th International Conference on Software Engineering, 2024) · cited 15× · AI/ML
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Learning in the Wild: Towards Leveraging Unlabeled Data for Effectively Tuning Pre-trained Code Models

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Learning in the Wild: Towards Leveraging Unlabeled Data for Effectively Tuning Pre-trained Code Models is a scholarly article[1].

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APA 4ort.xyz Knowledge Graph. (2026). Learning in the Wild: Towards Leveraging Unlabeled Data for Effectively Tuning Pre-trained Code Models. Retrieved May 24, 2026, from https://4ort.xyz/entity/learning-in-the-wild-towards-leveraging-unlabeled-data-for-effectively-tuning-pre-trained-code-models
MLA “Learning in the Wild: Towards Leveraging Unlabeled Data for Effectively Tuning Pre-trained Code Models.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/learning-in-the-wild-towards-leveraging-unlabeled-data-for-effectively-tuning-pre-trained-code-models.
BibTeX @misc{4ortxyz_learning-in-the-wild-towards-leveraging-unlabeled-data-for-effectively-tuning-pre-trained-code-models_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Learning in the Wild: Towards Leveraging Unlabeled Data for Effectively Tuning Pre-trained Code Models}}, year = {2026}, url = {https://4ort.xyz/entity/learning-in-the-wild-towards-leveraging-unlabeled-data-for-effectively-tuning-pre-trained-code-models}, note = {Accessed: 2026-05-24}}
LLM prompt According to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Learning in the Wild: Towards Leveraging Unlabeled Data for Effectively Tuning Pre-trained Code Models — https://4ort.xyz/entity/learning-in-the-wild-towards-leveraging-unlabeled-data-for-effectively-tuning-pre-trained-code-models (retrieved 2026-05-24)

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