Weiming Shen
YOU?
Author Swipe
View article: Prognostic implications of adverse events associated with CAR-T cell therapy: a population-based global observational study
Prognostic implications of adverse events associated with CAR-T cell therapy: a population-based global observational study Open
View article: An individual generalization framework based on independent samples towards a more reasonable fault diagnosis benchmark
An individual generalization framework based on independent samples towards a more reasonable fault diagnosis benchmark Open
View article: Leveraging Learning Bias for Noisy Anomaly Detection
Leveraging Learning Bias for Noisy Anomaly Detection Open
This paper addresses the challenge of fully unsupervised image anomaly detection (FUIAD), where training data may contain unlabeled anomalies. Conventional methods assume anomaly-free training data, but real-world contamination leads model…
View article: Rare Causes of Lynch Syndrome: EPCAM Deletion and MSH2 Inversion
Rare Causes of Lynch Syndrome: EPCAM Deletion and MSH2 Inversion Open
View article: The correlation between stiffness and viscoelasticity of the myometrium in adenomyosis: a prospective study
The correlation between stiffness and viscoelasticity of the myometrium in adenomyosis: a prospective study Open
There were statistically significant differences in the stiffness and water content of the inner, middle, and outer myometrium in patients with AM. Meanwhile, the stiffness of each myometrium and lesion, microvascular flow, and uterine siz…
View article: Towards High-Resolution 3D Anomaly Detection: A Scalable Dataset and Real-Time Framework for Subtle Industrial Defects
Towards High-Resolution 3D Anomaly Detection: A Scalable Dataset and Real-Time Framework for Subtle Industrial Defects Open
In industrial point cloud analysis, detecting subtle anomalies demands high-resolution spatial data, yet prevailing benchmarks emphasize low-resolution inputs. To address this disparity, we propose a scalable pipeline for generating realis…
View article: Mendelian randomization analysis of immune cell populations, serum metabolites and hepatocellular carcinoma risk
Mendelian randomization analysis of immune cell populations, serum metabolites and hepatocellular carcinoma risk Open
View article: MIA and CD163 as promising diagnostic biomarkers in vascular dementia: A multi-method study combining WGCNA, machine learning with validation in animal models and clinical samples
MIA and CD163 as promising diagnostic biomarkers in vascular dementia: A multi-method study combining WGCNA, machine learning with validation in animal models and clinical samples Open
Vascular dementia (VaD), the second most common form of dementia, lacks reliable biomarkers for early diagnosis. Here, we integrated weighted gene co-expression network analysis (WGCNA) with machine learning to identify novel biomarkers an…
View article: Asymptotic behavior of complete conformal metric near singular boundary
Asymptotic behavior of complete conformal metric near singular boundary Open
The boundary behavior of the singular Yamabe problem has been extensively studied near sufficiently smooth boundaries, while less is known about the asymptotic behavior of solutions near singular boundaries. In this paper, we study the asy…
View article: INP-Former++: Advancing Universal Anomaly Detection via Intrinsic Normal Prototypes and Residual Learning
INP-Former++: Advancing Universal Anomaly Detection via Intrinsic Normal Prototypes and Residual Learning Open
Anomaly detection (AD) is essential for industrial inspection and medical diagnosis, yet existing methods typically rely on ``comparing'' test images to normal references from a training set. However, variations in appearance and positioni…
View article: MLorc: Momentum Low-rank Compression for Memory Efficient Large Language Model Adaptation
MLorc: Momentum Low-rank Compression for Memory Efficient Large Language Model Adaptation Open
With increasing size of large language models (LLMs), full-parameter fine-tuning imposes substantial memory demands. To alleviate this, we propose a novel memory-efficient training paradigm called Momentum Low-rank compression (MLorc). The…
View article: Permissioned LLMs: Enforcing Access Control in Large Language Models
Permissioned LLMs: Enforcing Access Control in Large Language Models Open
In enterprise settings, organizational data is segregated, siloed and carefully protected by elaborate access control frameworks. These access control structures can completely break down if an LLM fine-tuned on the siloed data serves requ…
View article: Grain-sized moxibustion activates dendritic cells to enhance the antitumor immunity of cancer vaccines
Grain-sized moxibustion activates dendritic cells to enhance the antitumor immunity of cancer vaccines Open
View article: Revisiting Sparsity Constraint Under High-Rank Property in Partial Multi-Label Learning
Revisiting Sparsity Constraint Under High-Rank Property in Partial Multi-Label Learning Open
Partial Multi-Label Learning (PML) extends the multi-label learning paradigm to scenarios where each sample is associated with a candidate label set containing both ground-truth labels and noisy labels. Existing PML methods commonly rely o…
View article: Genome-wide Chromosome-specific Aneuploidy Engineering and Phenotypic Characterization with CRISPR-Taiji
Genome-wide Chromosome-specific Aneuploidy Engineering and Phenotypic Characterization with CRISPR-Taiji Open
SUMMARY Aneuploidy, the gain or loss of chromosomes, is prevalent in both normal and disease conditions, however, experimental approaches to engineer and study aneuploidy remain limited, leaving its functional significance under-characteri…
View article: Global regularity for the Dirichlet problem of Monge-Ampère equation in convex polytopes
Global regularity for the Dirichlet problem of Monge-Ampère equation in convex polytopes Open
We study the Dirichlet problem for Monge-Ampère equation in bounded convex polytopes. We give sharp conditions for the existence of global $C^2$ and $C^{2,α}$ convex solutions provided that a global $C^2$, convex subsolution exists.
View article: Label-Free Backdoor Attacks in Vertical Federated Learning
Label-Free Backdoor Attacks in Vertical Federated Learning Open
Vertical Federated Learning (VFL) involves multiple clients collaborating to train a global model, with distributed features of shared samples. While it becomes a critical privacy-preserving learning paradigm, its security can be significa…
View article: Apollo-Forecast: Overcoming Aliasing and Inference Speed Challenges in Language Models for Time Series Forecasting
Apollo-Forecast: Overcoming Aliasing and Inference Speed Challenges in Language Models for Time Series Forecasting Open
Encoding time series into tokens and using language models for processing has been shown to substantially augment the models' ability to generalize to unseen tasks. However, existing language models for time series forecasting encounter se…
View article: Tracking neural activity patterns during rapid high-altitude transitions
Tracking neural activity patterns during rapid high-altitude transitions Open
Rapid adaptation to dynamic changes in the environment is critical for human survival. Extensive studies have observed human behavior and brain activity in a stable environment, but there is still a lack of understanding of how our brain's…
View article: Dereflection Any Image with Diffusion Priors and Diversified Data
Dereflection Any Image with Diffusion Priors and Diversified Data Open
Reflection removal of a single image remains a highly challenging task due to the complex entanglement between target scenes and unwanted reflections. Despite significant progress, existing methods are hindered by the scarcity of high-qual…
View article: Exploring Intrinsic Normal Prototypes within a Single Image for Universal Anomaly Detection
Exploring Intrinsic Normal Prototypes within a Single Image for Universal Anomaly Detection Open
Anomaly detection (AD) is essential for industrial inspection, yet existing methods typically rely on ``comparing'' test images to normal references from a training set. However, variations in appearance and positioning often complicate th…
View article: Development of a New Method M2LC for Few-Slice-Annotated MRI Image Segmentation and Validation of its Performance on Multiple Datasets
Development of a New Method M2LC for Few-Slice-Annotated MRI Image Segmentation and Validation of its Performance on Multiple Datasets Open
View article: Agent‐based digital twins for collaborative machine intelligence solutions
Agent‐based digital twins for collaborative machine intelligence solutions Open
The deep integration of digital twins (DT) and agents is expected to open up new collaborative machine intelligence solutions. A new concept, namely, agent‐based digital twins (ADT), is proposed to establish a novel machine intelligence fr…
View article: VarAD: Lightweight High-Resolution Image Anomaly Detection via Visual Autoregressive Modeling
VarAD: Lightweight High-Resolution Image Anomaly Detection via Visual Autoregressive Modeling Open
This paper addresses a practical task: High-Resolution Image Anomaly Detection (HRIAD). In comparison to conventional image anomaly detection for low-resolution images, HRIAD imposes a heavier computational burden and necessitates superior…
View article: Deep Reinforcement Learning-based Multi-Objective Scheduling for Distributed Heterogeneous Hybrid Flow Shops with Blocking Constraints
Deep Reinforcement Learning-based Multi-Objective Scheduling for Distributed Heterogeneous Hybrid Flow Shops with Blocking Constraints Open
View article: Apollo-Forecast: Overcoming Aliasing and Inference Speed Challenges in Language Models for Time Series Forecasting
Apollo-Forecast: Overcoming Aliasing and Inference Speed Challenges in Language Models for Time Series Forecasting Open
Encoding time series into tokens and using language models for processing has been shown to substantially augment the models' ability to generalize to unseen tasks. However, existing language models for time series forecasting encounter se…
View article: LiftImage3D: Lifting Any Single Image to 3D Gaussians with Video Generation Priors
LiftImage3D: Lifting Any Single Image to 3D Gaussians with Video Generation Priors Open
Single-image 3D reconstruction remains a fundamental challenge in computer vision due to inherent geometric ambiguities and limited viewpoint information. Recent advances in Latent Video Diffusion Models (LVDMs) offer promising 3D priors l…
View article: The Impact of Artificial Intelligence on Economic Development: A Systematic Review
The Impact of Artificial Intelligence on Economic Development: A Systematic Review Open
Artificial Intelligence (AI) has emerged as a transformative force across various sectors, reshaping economies and societies globally. This review aims to provide a systematic analysis of the existing literature on the impact of AI on econ…
View article: A Discrete Brain Storm Optimization Algorithm for Hybrid Flowshop Scheduling Problems with Batch Production at Last Stage in the Steelmaking-Refining-Continuous Casting Process
A Discrete Brain Storm Optimization Algorithm for Hybrid Flowshop Scheduling Problems with Batch Production at Last Stage in the Steelmaking-Refining-Continuous Casting Process Open
The iron and steel industry is energy-intensive due to the large volume of steel produced and its high-temperature and high-weight characteristics, sensors such as high-temperature application sensors can be utilized to collect production …
View article: On the Training Convergence of Transformers for In-Context Classification of Gaussian Mixtures
On the Training Convergence of Transformers for In-Context Classification of Gaussian Mixtures Open
Although transformers have demonstrated impressive capabilities for in-context learning (ICL) in practice, theoretical understanding of the underlying mechanism that allows transformers to perform ICL is still in its infancy. This work aim…