activity
20242026
most citedEvaluation of OpenAI o1: Opportunities and Challenges of AGI

22 citations · 38 across the 18 of their papers we have counts for

collaborators

18 papers

stat.ML2026

Complex Problem Solving in Large Language Models: A Statistical Control Survey and Diagnostic Framework

Jiazhang Cai, Tao Wang, Ruidong Zhang +35

Complex problem solving (CPS) with large language models (LLMs) is often framed as a matter of stronger reasoning or longer generation. Yet early-step error amplification, prompt b…

q-bio.NC2026

SC-TauPath: A Structural Connectivity Attribution Framework for Mapping Tau Propagation Pathways in Alzheimer's Disease

Jing Zhang, Norman Scheel, Minheng Chen +5

Understanding how structural connections are associated with tau propagation in Alzheimer's disease (AD) remains a central open question, yet existing computational models either r…

q-bio.NC2026

Learning Cross-Atlas Consistent Brain Disorder Representations via Disentangled Multi-Atlas Functional Connectivity Learning

Minheng Chen, Chao Cao, Jing Zhang +2

Functional connectivity (FC) derived from resting-state fMRI is widely used to characterize large-scale brain network alterations in neurological and psychiatric disorders. However…

q-bio.NC2026

Probability-Invariant Random Walk Learning on Gyral Folding-Based Cortical Similarity Networks for Alzheimer's and Lewy Body Dementia Diagnosis

Minheng Chen, Tong Chen, Chao Cao +4

Alzheimer's disease (AD) and Lewy body dementia (LBD) present overlapping clinical features yet require distinct diagnostic strategies. While neuroimaging-based brain network analy…

q-bio.NC2026

Community-Level Modeling of Gyral Folding Patterns for Robust and Anatomically Informed Individualized Brain Mapping

Minheng Chen, Tong Chen, Yan Zhuang +5

Cortical folding exhibits substantial inter-individual variability while preserving stable anatomical landmarks that enable fine-scale characterization of cortical organization. Am…

cs.CV2025

DCMM-Transformer: Degree-Corrected Mixed-Membership Attention for Medical Imaging

Huimin Cheng, Xiaowei Yu, Shushan Wu +7

Medical images exhibit latent anatomical groupings, such as organs, tissues, and pathological regions, that standard Vision Transformers (ViTs) fail to exploit. While recent work l…

cs.CV2025

Bridging Brain Connectomes and Clinical Reports for Early Alzheimer's Disease Diagnosis

Jing Zhang, Xiaowei Yu, Minheng Chen +8

Integrating brain imaging data with clinical reports offers a valuable opportunity to leverage complementary multimodal information for more effective and timely diagnosis in pract…

cs.AI2025★ 2 cited

Alignment and Safety in Large Language Models: Safety Mechanisms, Training Paradigms, and Emerging Challenges

Haoran Lu, Luyang Fang, Ruidong Zhang +47

Due to the remarkable capabilities and growing impact of large language models (LLMs), they have been deeply integrated into many aspects of society. Thus, ensuring their alignment…

cs.LG2025

Domain-Adaptive Diagnosis of Lewy Body Disease with Transferability Aware Transformer

Xiaowei Yu, Jing Zhang, Tong Chen +8

Lewy Body Disease (LBD) is a common yet understudied form of dementia that imposes a significant burden on public health. It shares clinical similarities with Alzheimer's disease (…

cs.CL2025★ 1 cited

Knowledge Distillation and Dataset Distillation of Large Language Models: Emerging Trends, Challenges, and Future Directions

Luyang Fang, Xiaowei Yu, Jiazhang Cai +23

The exponential growth of Large Language Models (LLMs) continues to highlight the need for efficient strategies to meet ever-expanding computational and data demands. This survey p…

q-bio.NC2025

GyralNet Subnetwork Partitioning via Differentiable Spectral Modularity Optimization

Yan Zhuang, Minheng Chen, Chao Cao +7

Understanding the structural and functional organization of the human brain requires a detailed examination of cortical folding patterns, among which the three-hinge gyrus (3HG) ha…

q-bio.NC2025

Core-Periphery Principle Guided State Space Model for Functional Connectome Classification

Minheng Chen, Xiaowei Yu, Jing Zhang +7

Understanding the organization of human brain networks has become a central focus in neuroscience, particularly in the study of functional connectivity, which plays a crucial role…

cs.LG2025

BrainNet-MoE: Brain-Inspired Mixture-of-Experts Learning for Neurological Disease Identification

Jing Zhang, Xiaowei Yu, Tong Chen +8

The Lewy body dementia (LBD) is the second most common neurodegenerative dementia after Alzheimer's disease (AD). Early differentiation between AD and LBD is crucial because they r…

eess.IV2025★ 1 cited

Classification of Mild Cognitive Impairment Based on Dynamic Functional Connectivity Using Spatio-Temporal Transformer

Jing Zhang, Yanjun Lyu, Xiaowei Yu +7

Dynamic functional connectivity (dFC) using resting-state functional magnetic resonance imaging (rs-fMRI) is an advanced technique for capturing the dynamic changes of neural activ…

eess.IV2025★ 8 cited

Brain-Adapter: Enhancing Neurological Disorder Analysis with Adapter-Tuning Multimodal Large Language Models

Jing Zhang, Xiaowei Yu, Yanjun Lyu +7

Understanding brain disorders is crucial for accurate clinical diagnosis and treatment. Recent advances in Multimodal Large Language Models (MLLMs) offer a promising approach to in…

cs.CV2024

Using Structural Similarity and Kolmogorov-Arnold Networks for Anatomical Embedding of Cortical Folding Patterns

Minheng Chen, Chao Cao, Tong Chen +7

The 3-hinge gyrus (3HG) is a newly defined folding pattern, which is the conjunction of gyri coming from three directions in cortical folding. Many studies demonstrated that 3HGs c…

cs.CL2024★ 22 cited

Evaluation of OpenAI o1: Opportunities and Challenges of AGI

Tianyang Zhong, Zhengliang Liu, Yi Pan +74

This comprehensive study evaluates the performance of OpenAI's o1-preview large language model across a diverse array of complex reasoning tasks, spanning multiple domains, includi…

cs.CL2024★ 4 cited

GP-GPT: Large Language Model for Gene-Phenotype Mapping

Yanjun Lyu, Zihao Wu, Lu Zhang +11

Pre-trained large language models(LLMs) have attracted increasing attention in biomedical domains due to their success in natural language processing. However, the complex traits a…