15 citations · 17 across the 3 of their papers we have counts for
4 papers
Defense-in-Depth for LLMs: Evaluating Memory Gates Against Activation-Induced and Memory-Induced Sycophancy
Ritvij Sharma, Russell Dlugosz, Ryan Zhou +1
Long-term memory allows Large Language Models (LLMs) to maintain personalized context across interactions, but retrieved user history can induce memory-induced sycophancy, causing…
Self-Reports Are Not Verification: Environment-Grounded Auditing of LLM Operators in Evolutionary Search
Enrong Pan, Ryan Zhou, Ting Hu
Language model agents increasingly propose actions, observe external feedback, and explain their own behavior. Their confidence and rationales are convenient monitoring signals, bu…
Evolutionary Computation and Explainable AI: A Roadmap to Understandable Intelligent Systems
Ryan Zhou, Jaume Bacardit, Alexander Brownlee +7
Artificial intelligence methods are being increasingly applied across various domains, but their often opaque nature has raised concerns about accountability and trust. In response…
Evolutionary approaches to explainable machine learning
Ryan Zhou, Ting Hu
Machine learning models are increasingly being used in critical sectors, but their black-box nature has raised concerns about accountability and trust. The field of explainable art…