9 papers
Confidence-Orchestrated Self-Evolution against Uncertain LLM Feedback
Bowen Wei, Nan Wang, Yuqing Zhou +2
Self-evolving large language models (LLMs) learn by generating their own training tasks and solutions, reducing reliance on human-curated supervision. However, in many reasoning do…
A Logical-Rule Autoencoder for Interpretable Recommendations
Jinhao Pan, Bowen Wei, Ziwei Zhu
Most deep learning recommendation models operate as black boxes, relying on latent representations that obscure their decision process. This lack of intrinsic interpretability rais…
ClawSafety: "Safe" LLMs, Unsafe Agents
Bowen Wei, Yunbei Zhang, Jinhao Pan +5
Personal AI agents like OpenClaw run with elevated privileges on users' local machines, where a single successful prompt injection can leak credentials, redirect financial transact…
Interpretable Classification via a Rule Network with Selective Logical Operators
Bowen Wei, Ziwei Zhu
We introduce the Rule Network with Selective Logical Operators (RNS), a novel neural architecture that employs \textbf{selective logical operators} to adaptively choose between AND…
Context-Aware Decoding for Faithful Vision-Language Generation
Mehrdad Fazli, Bowen Wei, Ziwei Zhu
Hallucinations, generating responses inconsistent with the visual input, remain a critical limitation of large vision-language models (LVLMs), especially in open-ended tasks such a…
CORTEX: Collaborative LLM Agents for High-Stakes Alert Triage
Bowen Wei, Yuan Shen Tay, Howard Liu +4
Security Operations Centers (SOCs) are overwhelmed by tens of thousands of daily alerts, with only a small fraction corresponding to genuine attacks. This overload creates alert fa…