1 citations · 1 across the 4 of their papers we have counts for
6 papers
Streamlined Reflective Evolution for Task-Adaptive Self-Refinement Pipelines
Xiaofan Zhou, Lu Cheng
Reflective prompt optimization improves large language model (LLM) systems without updating model weights, but fixed architectures constrain how self-refinement is organized. We in…
What Should the Reflector See? An Empirical Study of Evidence in Reflective Prompt Optimization
Xiaofan Zhou, Lu Cheng
Reflective prompt optimization revises instructions using examples of a model's behavior, but which evidence the reflector should receive remains unclear. We study evidence composi…
Robust Uncertainty Quantification for Self-Evolving Large Language Models via Continual Domain Pretraining
Xiaofan Zhou, Lu Cheng
Continual Learning (CL) is essential for enabling self-evolving large language models (LLMs) to adapt and remain effective amid rapid knowledge growth. Yet, despite its importance,…
Smart Trial: Evaluating the Use of Large Language Models for Recruiting Clinical Trial Participants via Social Media
Xiaofan Zhou, Zisu Wang, Janice Krieger +2
Clinical trials (CT) are essential for advancing medical research and treatment, yet efficiently recruiting eligible participants -- each of whom must meet complex eligibility crit…
Accelerating Causal Network Discovery of Alzheimer Disease Biomarkers via Scientific Literature-based Retrieval Augmented Generation
Xiaofan Zhou, Liangjie Huang, Pinyang Cheng +4
The causal relationships between biomarkers are essential for disease diagnosis and medical treatment planning. One notable application is Alzheimer's disease (AD) diagnosis, where…
Conformal Prediction: A Data Perspective
Xiaofan Zhou, Baiting Chen, Yu Gui +1
Conformal prediction (CP), a distribution-free uncertainty quantification (UQ) framework, reliably provides valid predictive inference for black-box models. CP constructs predictio…