5 citations · 6 across the 4 of their papers we have counts for
4 papers
Don't Make Models Guess Security and Safety: Symbolic Guardrails for Domain-Specific AI Agents
Yining Hong, Yining She, Eunsuk Kang +2
There is increasing interest in integrating AI agents that invoke tools into domain-specific commercial software, where unintended tool calls can cause serious security and safety…
Towards Verifiably Safe Tool Use for LLM Agents
Aarya Doshi, Yining Hong, Congying Xu +3
Large language model (LLM)-based AI agents extend LLM capabilities by enabling access to tools such as data sources, APIs, search engines, code sandboxes, and even other agents. Wh…
From Hazard Identification to Controller Design: Proactive and LLM-Supported Safety Engineering for ML-Powered Systems
Yining Hong, Christopher S. Timperley, Christian Kästner
Machine learning (ML) components are increasingly integrated into software products, yet their complexity and inherent uncertainty often lead to unintended and hazardous consequenc…
What Is Wrong with My Model? Identifying Systematic Problems with Semantic Data Slicing
Chenyang Yang, Yining Hong, Grace A. Lewis +2
Machine learning models make mistakes, yet sometimes it is difficult to identify the systematic problems behind the mistakes. Practitioners engage in various activities, including…