Retrieval-augmented generation for ai-generated content: A survey

P Zhao, H Zhang, Q Yu, Z Wang, Y Geng, F Fu… - arXiv preprint arXiv …, 2024 - arxiv.org
The development of Artificial Intelligence Generated Content (AIGC) has been facilitated by
advancements in model algorithms, scalable foundation model architectures, and the …

NLPerturbator: Studying the Robustness of Code LLMs to Natural Language Variations

J Chen, Z Li, X Hu, X Xia - arXiv preprint arXiv:2406.19783, 2024 - arxiv.org
Large language models (LLMs) achieve promising results in code generation based on a
given natural language description. They have been integrated into open-source projects …

STALL+: Boosting LLM-based Repository-level Code Completion with Static Analysis

J Liu, Y Chen, M Liu, X Peng, Y Lou - arXiv preprint arXiv:2406.10018, 2024 - arxiv.org
Repository-level code completion is challenging as it involves complicated contexts from
multiple files in the repository. To date, researchers have proposed two technical categories …

[PDF][PDF] Requirements Engineering for Trustworthy Human-AI Synergy in Software Engineering 2.0

D Lo - mysmu.edu
Software Engineering 2.0 envisions trustworthy and synergistic collaborations between
humans and AI agents that are diverse, responsible, and autonomous, aiming to build the …