Dan Liu

ALRcallerX: Creating data-driven simulations by bridging R-based machine learning and AI-powered modeling in AnyLogic

Hang Shao, Shan-e-hyder Soomro, Xiaotao Shi, Dan Liu, Yunfei Liu, Chunpeng Bao, et al.

Central neuroendocrine dysregulation in ischaemic stroke sequelae: pathophysiological mechanisms—a narrative review

Han Gong, Dan Liu, Xiang-Zheng Wang, Jia‐Sheng Rao, Xiao-Xia Du

Ischemic stroke (IS) prognosis is frequently compromised by secondary systemic and neuropsychiatric complications extending beyond the initial brain injury. The hypothalamic–pituitary–adrenal (HPA) axis, the primary neuroendocrine regulator, plays a pivotal yet underappreciated r…Read more

CatalogAgent: A Supervisor-mediated Self-Learning System Enabling Context Engineering for GenAI Models

Zhu Cheng, Zhenming Wang, Yu, Tang, Dan Liu, Bryan Zhang, et al.

Product catalogs are the backbone of e-commerce sites, yet a large number of structured attributes (SAs) -- such as material, color, and shape -- often have missing values. Typically, SA values are extracted from product information, including titles and descriptions. While LLM-b…Read more

PGUDA: Pressure-Guided Unsupervised Domain Adaptation with Cross-Modal Knowledge Distillation for sEMG-Based Gesture Recognition

Yurui Liu, Xiao-Cong Zhong, Qisong Wang, Xuefu Wang, Dan Liu, Jinwei Sun

Surface electromyography (sEMG)-based gesture recognition has emerged as a promising technology for natural human-computer interaction. However, its practical deployment remains challenging due to severe performance degradation caused by feature distribution discrepancies across…Read more

DRIFT: Difficulty Routing Self-DIstillation with Rhythm-Gated Exploration and Success BuFfer Training

Haisen Luo, Yiwei Liu, Haoning Wang, Dan Liu, Junxi Yin, Haotian Wang, et al.

Enabling large language models to achieve stable self-improvement without external expert supervision remains a central challenge in complex reasoning tasks. Existing self-distillation and reinforcement learning methods lack explicit mechanisms for tracking problem-level learning…Read more