2 citations · 4 across the 19 of their papers we have counts for
7 papers · 1 filter
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…
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…
AutoLab: Can Frontier Models Solve Long-Horizon Auto Research and Engineering Tasks?
Zhangchen Xu, Junda Chen, Yue Huang +16
Scientific and engineering progress is fundamentally a long-horizon iterative process: proposing changes, running experiments, measuring outcomes, and continuously refining artifac…
Interactive Evaluation Requires a Design Science
Keyang Xuan, Peiyang Song, Pan Lu +10
AI evaluation is undergoing a structural change. Large language models (LLMs) are increasingly deployed as systems that act over time through tools, environments, users, and other…
Quantifying Trust: Financial Risk Management for Trustworthy AI Agents
Wenyue Hua, Tianyi Peng, Chi Wang +4
Prior work on trustworthy AI emphasizes model-internal properties such as bias mitigation, adversarial robustness, and interpretability. As AI systems evolve into autonomous agents…
ReCAP: Recursive Context-Aware Reasoning and Planning for Large Language Model Agents
Zhenyu Zhang, Tianyi Chen, Weiran Xu +2
Long-horizon tasks requiring multi-step reasoning and dynamic re-planning remain challenging for large language models (LLMs). Sequential prompting methods are prone to context dri…