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Chen Zhang

8 papers indexed

openalexPLoS Computational Biology2026-07-23

A cost-optimized 5-protein panel revolutionizes systemic lupus erythematosus diagnosis

Wenhua Lv, Zhenwei Shang, Chen Sun, Yuping Zou, Siyu Wei, Haiyan Chen, et al.

Early diagnosis of systemic lupus erythematosus (SLE) is hindered by a lack of reliable biomarkers. This study sought to identify and evaluate diagnostic plasma protein biomarkers for SLE. We analyzed plasma protein profiles, polygenic risk scores (PRS), and clinical data from 54…

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arxivcs.AI2026-07-19

Bridging the Information Gap: Semantic Densification and Hindsight Distillation for Cold-Start Prediction

Hao Duong Le, Yifei Gao, Huan Li, Lun Jiang, Chen Bai, Ke Xing, et al.

New-user cold-start is a critical bottleneck for e-commerce platforms: predicting user lifetime value (LTV) and conversion rate (CVR) for users with sparse interaction history. Two prior directions -- LLM-based semantic augmentation and learning using privileged information (LUPI…

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arxivcs.ARcs.AI2026-07-14

Full-Pipeline Inference Optimization for MiMo-V2.5 Series: Pushing Hybrid SWA Efficiency to the Limit

Xiaomi MiMo Team, Anqi Liu, Aoxin Ma, Bo Chen, Bo Yang, Chen Wang, et al.

We present a full-pipeline inference optimization for the MiMo-V2.5 model family, which combines Hybrid Sliding Window Attention (Hybrid SWA), sparse Mixture-of-Experts (MoE), and multimodal encoders. While Hybrid SWA can ideally reduce both attention compute and KVCache storage…

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arxiveess.SY2026-07-09

On the Convergence of the Current-Constrained Power Angle Curve of Virtual Admittance-Based Grid Forming Converters

Haoxiang Zong, Chen Zhang, Yu Zhang, Xu Cai, Marta Molinas

The current-constrained power-angle curve (PAC) is crucial for the transient synchronization stability (TSS) analysis of virtual admittance-based (VA) grid-forming (GFM) converters. Its formulation and application rely on the quasi-steady-state assumption critically, i.e., the ac…

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arxiveess.SY2026-07-07

Generalized Feedback Control Modeling Method for Control-Driven Converter Systems

Chen Zhang, Haoxiang Zong, Xu Cai, Marta Molinas

Converters-based systems like wind farms manifest themselves as control-intensive systems, where control-driven stability issues frequently occur, e.g., oscillations. Such issues are popularly studied via circuit impedance-based methods. However, given its implicit controller mod…

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arxivcs.CV2026-07-06

ICME 2026 Grand Challenge on Cross-Scenario Defect Detection and Fine-Grained Severity Grading for High-Precision Manufacturing

Wei Sun, Weixia Zhang, Linhan Cao, Mingkai Lu, Xiongkuo Min, Xiaoping Zhang, et al.

This paper presents the IEEE International Conference on Multimedia and Expo (ICME) 2026 Grand Challenge on Cross-Scenario Defect Detection and Fine-Grained Severity Grading for High-Precision Manufacturing. The challenge is motivated by two key limitations of existing industrial…

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arxivcs.CLcs.AI2026-06-28

To Reason or to Fabricate: Reasoning Without Shortcuts via Hint-Anchored Pairwise Aggregation

Jiuheng Lin, Chen Zhang, Yansong Feng

While reinforcement learning (RL) significantly enhances LLM reasoning, its efficacy is severely undermined by Pre-RL data overlap, where RL datasets overlap with pretraining or SFT corpora, causing models to exploit shortcuts by memorizing correct answers and fabricating post-ho…

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crossrefTomography2024-08-12Cited by 20

Machine Learning and Deep Learning Approaches in Lifespan Brain Age Prediction: A Comprehensive Review

Yutong Wu, Hongjian Gao, Chen Zhang, Xiangge Ma, Xinyu Zhu, Shuicai Wu, et al.

The concept of ‘brain age’, derived from neuroimaging data, serves as a crucial biomarker reflecting cognitive vitality and neurodegenerative trajectories. In the past decade, machine learning (ML) and deep learning (DL) integration has transformed the field, providing advanced m…

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