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Found 5 papers, 1 papers with code
Generative AI for Requirements Engineering: A Systematic Literature Review
Results: The most salient findings include i) a predominant focus on the early stages of RE, particularly the elicitation and analysis of requirements, indicating potential for expansion into later phases; ii) the dominance of large language models, especially the GPT series, highlighting the need for diverse AI approaches; and iii) persistent challenges in domain-specific applications and the interpretability of AI-generated outputs, underscoring areas requiring further research and development.
Refining GPT-3 Embeddings with a Siamese Structure for Technical Post Duplicate Detection
When applied to the dataset we constructed with a recent Stack Overflow dump, our approach attains a Top-1, Top-5, and Top-30 accuracy of 23. 1%, 43. 9%, and 68. 9%, respectively.
Machine Learning Application Development: Practitioners' Insights
In this paper, we report about a survey that aimed to understand the challenges and best practices of ML application development.
Preliminary Systematic Literature Review of Machine Learning System Development Process
Previous machine learning (ML) system development research suggests that emerging software quality attributes are a concern due to the probabilistic behavior of ML systems.
Studying Software Engineering Patterns for Designing Machine Learning Systems
Machine-learning (ML) techniques have become popular in the recent years.
