2 citations · 2 across the 3 of their papers we have counts for
3 papers
cs.AI2026
AISPA: User-Centric System Prompt Auditing for Large Language Model Applications
Xiangning Lin, Shenzhe Zhu, Shu Yang +23
System prompts are instructions configured by developers to govern the behaviors of foundation models in AI applications. They are used throughout commercial AI products, but are r…
cs.AI2026
Interactive Task Alignment as a POMDP
Andy Dai, Zexue He, Zhenyu Zhang +2
Current benchmarks for language models primarily evaluate execution on fully specified tasks. However, real user tasks are often ambiguous. Users arrive with incomplete, explorator…
cs.AI2024★ 2 cited
Responsible AI in Construction Safety: Systematic Evaluation of Large Language Models and Prompt Engineering
Farouq Sammour, Jia Xu, Xi Wang +2
Construction remains one of the most hazardous sectors. Recent advancements in AI, particularly Large Language Models (LLMs), offer promising opportunities for enhancing workplace…