Lessons from the NLBSE 2024 Competition: Towards Building Efficient Models for GitHub Issue Classification
Author:
Affiliation:
1. Department of Systems and Computing Engineering, Universidad de los Andes, Bogotá, Colombia
Publisher
ACM
Link
https://dl.acm.org/doi/pdf/10.1145/3643787.3648040
Reference7 articles.
1. Few-Shot Learning for Issue Report Classification
2. Rafael Kallis, Giuseppe Colavito, Ali Al-Kaswan, Luca Pascarella, Oscar Chaparro, and Pooja Rani. 2024. The NLBSE'24 Tool Competition. In Proceedings of The 3rd International Workshop on Natural Language-based Software Engineering (NLBSE'24).
3. Ticket Tagger: Machine Learning Driven Issue Classification
4. Predicting issue types on GitHub
5. Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks
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