5 papers
NormCode: A Semi-Formal Language for Auditable AI Planning
Xin Guan, Yunshan Li, Zekun Wu +1
As AI systems move into high stakes domains such as legal reasoning, medical diagnosis, and financial decision making, regulators and practitioners increasingly demand auditability…
Knowledge Collapse in LLMs: When Fluency Survives but Facts Fail under Recursive Synthetic Training
Figarri Keisha, Zekun Wu, Ze Wang +2
Large language models increasingly rely on synthetic data due to human-written content scarcity, yet recursive training on model-generated outputs leads to model collapse, a degene…
Personality as a Probe for LLM Evaluation: Method Trade-offs and Downstream Effects
Gunmay Handa, Zekun Wu, Adriano Koshiyama +1
Personality manipulation in large language models (LLMs) is increasingly applied in customer service and agentic scenarios, yet its mechanisms and trade-offs remain unclear. We pre…
MPF: Aligning and Debiasing Language Models post Deployment via Multi Perspective Fusion
Xin Guan, PeiHsin Lin, Zekun Wu +4
Multiperspective Fusion (MPF) is a novel posttraining alignment framework for large language models (LLMs) developed in response to the growing need for easy bias mitigation. Built…
LibVulnWatch: A Deep Assessment Agent System and Leaderboard for Uncovering Hidden Vulnerabilities in Open-Source AI Libraries
Zekun Wu, Seonglae Cho, Umar Mohammed +7
Open-source AI libraries are foundational to modern AI systems, yet they present significant, underexamined risks spanning security, licensing, maintenance, supply chain integrity,…