#systematic-review News & Analysis

4 articles tagged with #systematic-review. AI-curated summaries with sentiment analysis and key takeaways from 50+ sources.

4 articles

AINeutralarXiv – CS AI · 6h ago7/10

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Bridging Generation and Training: A Systematic Review of Quality Issues in LLMs for Code

A systematic review of 114 studies reveals that code quality defects in large language models stem primarily from training data imperfections rather than model limitations alone. The research establishes a taxonomy linking 18 propagation mechanisms between data quality issues and generated code failures, while advocating for proactive data governance over reactive post-generation filtering.

AIBullisharXiv – CS AI · Apr 136/10

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TiAb Review Plugin: A Browser-Based Tool for AI-Assisted Title and Abstract Screening

Researchers developed TiAb Review Plugin, an open-source Chrome extension that enables AI-assisted screening of academic titles and abstracts without requiring server subscriptions or coding skills. The tool combines Google Sheets for collaboration, Google's Gemini API for LLM-based screening, and an in-browser machine learning algorithm achieving 94-100% recall, demonstrating practical viability for systematic literature reviews.

🧠 Gemini

AINeutralarXiv – CS AI · Mar 276/10

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Factors Influencing the Quality of AI-Generated Code: A Synthesis of Empirical Evidence

A systematic literature review of 24 studies reveals that AI-generated code quality depends on multiple factors including prompt design, task specification, and developer expertise. The research shows variable outcomes for code correctness, security, and maintainability, indicating that AI-assisted development requires careful human oversight and validation.

AINeutralarXiv – CS AI · Mar 36/103

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Toward Youth-Centered Privacy-by-Design in Smart Devices: A Systematic Review

A systematic review of 122 academic papers reveals significant gaps in privacy protection for youth using AI-enabled smart devices, with technical solutions dominating research (67%) while policy enforcement and educational integration remain underdeveloped. The study recommends a multi-stakeholder approach involving policymakers, manufacturers, and educators to create comprehensive privacy ecosystems for young users.