程力｜湖北大学｜学者主页

2023

Wei Xie, Bo Wang, Cheng Li, Dongming Xie, Jared Auclair

Naval Research Logistics，Vol. 690, No. 3

Yuming Xu, Hengyu Liang, Jin Li, Shuotao Xu, Qi Chen, Qianxi Zhang, Cheng Li, Ziyue Yang, Fan Yang, Yuqing Yang, Peng Cheng, Mao Yang

Weijian Huang, Cheng Li, Hao Yang, Jiarun Liu, Yong Liang, Hairong Zheng, Shanshan Wang

arXiv preprint

DOI

2023

Large Language Models Understand and Can be Enhanced by Emotional Stimuli

Cheng Li, Jindong Wang, Yixuan Zhang, Kaijie Zhu, Wenxin Hou, Jianxun Lian, Fang Luo, Qiang Yang, Xing Xie

arXiv preprint

2023

Understand Data Preprocessing for Effective End-to-End Training of Deep Neural Networks

Ping Gong, Yuxin Ma, Cheng Li, Xiaosong Ma, Sam H. Noh

arXiv preprint

2023

Generalizable Learning Reconstruction for Accelerating MR Imaging via Federated Neural Architecture Search

Ruoyou Wu, Cheng Li, Juan Zou, Shanshan Wang

arXiv preprint

2023

PBFormer: Capturing Complex Scene Text Shape with Polynomial Band Transformer

A coarse-to-fine framework for unsupervised multi-contrast MR image deformable registration with dual consistency constraint

Weijian Huang, Hao Yang, Xinfeng Liu, Cheng Li, Ian Zhang, Rongpin Wang, Hairong Zheng, Shanshan Wang

arXiv preprint

DOI

2020

Beyond 512 Tokens: Siamese Multi-depth Transformer-based Hierarchical Encoder for Long-Form Document Matching

Liu Yang, Mingyang Zhang, Cheng Li, Michael Bendersky, Marc Najork

arXiv preprint

DOI

2020

Towards in-store multi-person tracking using head detection and track heatmaps

Aibek Musaev, Jiangping Wang, Liang Zhu, Cheng Li, Yi Chen, Jialin Liu, Wanqi Zhang, Juan Mei, De Wang

arXiv preprint

2020

Annotation-efficient deep learning for automatic medical image segmentation

Shanshan Wang, Cheng Li, Rongpin Wang, Zaiyi Liu, Meiyun Wang, Hongna Tan, Yaping Wu, Xinfeng Liu, Hui Sun, Rui Yang, Xin Liu, Jie Chen, Huihui Zhou, Ismail Ben Ayed, Hairong Zheng

arXiv preprint

DOI

2019

TSGformer: A Unified Temporal-Spatial Graph Transformer with Adaptive Cross-Scale Modeling for Multivariate Time Series

Nipping trouble in the bud: A proactive tourism recommender system

FedCSA: Enhancing Federated Unlearning Efficiency Through Adaptive Clustering Under Data Heterogeneity

Shanghai Transport Carbon Emission Forecasting Study Based on CEEMD-IWOA-KELM Model

A Deep Learning-Based Animation Video Image Data Anomaly Detection and Recognition Algorithm

Evolutionary Computation in bioinformatics: A survey

Disentangling Client Contributions: Improving Federated Learning Accuracy in the Presence of Heterogeneous Data

FedCSA: Boosting the Convergence Speed of Federated Unlearning under Data Heterogeneity

Methods to balance the exploration and exploitation in Differential Evolution from different scales: A survey

Improving SHADE with a Linear Reduction P Value and a Random Jumping Strategy

Interpretable biomanufacturing process risk and sensitivity analyses for quality-by-design and stability control

预印本

Low Light Image Enhancement Challenge at NTIRE 2026

Beyond Semantic Organization: Memory as Execution State Management for Long-Horizon Agents

PICS: Pairwise Image Compositing with Spatial Interactions

Crystal-KV: Efficient KV Cache Management for Chain-of-Thought LLMs via Answer-First Principle

ForestHG-Trace: Traceable Long-Horizon Ecological Reasoning over Large-Scale Forest Scenes

The Second LoViF 2026 Challenge on Real-World All-in-One Image Restoration: Methods and Results

Incremental Consistency Execution for Autonomous Intelligent Systems

Neuro-Symbolic Verification on Instruction Following of LLMs

Train What You Deploy:Token-Faithful Post-Training of a Production Coding

Capability-Driven Self-Evolution of Agent Memory

Bias-constrained multimodal intelligence for equitable and reliable clinical AI

CentroidKV: Efficient Long-Context LLM Inference via KV Cache Clustering

Distribution Preference Optimization: A Fine-grained Perspective for LLM Unlearning

KunLunBaizeRAG: Reinforcement Learning Driven Inference Performance Leap for Large Language Models

Video-VoT-R1: An efficient video inference model integrating image packing and AoE architecture

NTIRE 2025 Challenge on RAW Image Restoration and Super-Resolution

BOOTPLACE: Bootstrapped Object Placement with Detection Transformers

A Diffusion-Driven Temporal Super-Resolution and Spatial Consistency Enhancement Framework for 4D MRI imaging

DynaServe: Unified and Elastic Execution for Dynamic Disaggregated LLM Serving

Let It Flow: Agentic Crafting on Rock and Roll, Building the ROME Model within an Open Agentic Learning Ecosystem

KunlunBaize: LLM with Multi-Scale Convolution and Multi-Token Prediction Under TransformerX Framework

BigMac: A Communication-Efficient Mixture-of-Experts Model Structure for Fast Training and Inference

FLUX.1 Kontext: Flow Matching for In-Context Image Generation and Editing in Latent Space

Kimi k1.5: Scaling Reinforcement Learning with LLMs

MVT: Mask-Grounded Vision-Language Models for Taxonomy-Aligned Land-Cover Tagging

Enhancing Representation in Medical Vision-Language Foundation Models via Multi-Scale Information Extraction Techniques

Knowledge-driven deep learning for fast MR imaging: undersampled MR image reconstruction from supervised to un-supervised learning

VPTQ: Extreme Low-bit Vector Post-Training Quantization for Large Language Models

Multimodal self-supervised learning for lesion localization

SPFresh: Incremental In-Place Update for Billion-Scale Vector Search

Watch Every Step! LLM Agent Learning via Iterative Step-Level Process Refinement

Bridging the Preference Gap between Retrievers and LLMs

LESEN: Label-Efficient deep learning for Multi-parametric MRI-based Visual Pathway Segmentation

MLIP: Medical Language-Image Pre-training with Masked Local Representation Learning

Modality Exchange Network for Retinogeniculate Visual Pathway Segmentation

Automating Vessel Segmentation in the Heart and Brain: A Trend to Develop Multi-Modality and Label-Efficient Deep Learning Techniques

Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context

AID-DTI: Accelerating High-fidelity Diffusion Tensor Imaging with Detail-Preserving Model-based Deep Learning

Simultaneous q-Space Sampling Optimization and Reconstruction for Fast and High-fidelity Diffusion Magnetic Resonance Imaging

Enhancing the vision-language foundation model with key semantic knowledge-emphasized report refinement

Large Language Models Understand and Can be Enhanced by Emotional Stimuli

Understand Data Preprocessing for Effective End-to-End Training of Deep Neural Networks

Generalizable Learning Reconstruction for Accelerating MR Imaging via Federated Neural Architecture Search

PBFormer: Capturing Complex Scene Text Shape with Polynomial Band Transformer

Automated Evaluation of Personalized Text Generation using Large Language Models

RestGPT: Connecting Large Language Models with Real-World RESTful APIs

ZeroQuant-V2: Exploring Post-training Quantization in LLMs from Comprehensive Study to Low Rank Compensation

MGA: Medical generalist agent through text-guided knowledge transformation

Tessel: Boosting Distributed Execution of Large DNN Models via Flexible Schedule Search

CrossZoom: Simultaneously Motion Deblurring and Event Super-Resolving

Globally Optimal Solutions to a Class of Fractional Optimization Problems Based on Proximal Gradient Algorithm

Cross-Modal Object Tracking via Modality-Aware Fusion Network and A Large-Scale Dataset

FedAutoMRI: Federated Neural Architecture Search for MR Image Reconstruction

Model-based Federated Learning for Accurate MR Image Reconstruction from Undersampled k-space Data

Gemini: A Family of Highly Capable Multimodal Models

Self-distillation Regularized Connectionist Temporal Classification Loss for Text Recognition: A Simple Yet Effective Approach

Enhancing Scalability in Bayesian Nonparametric Factor Analysis of Spatiotemporal Data

Collaborative Learning for Annotation-Efficient Volumetric MR Image Segmentation

PARCEL: Physics-based Unsupervised Contrastive Representation Learning for Multi-coil MR Imaging

Random-LTD: Random and Layerwise Token Dropping Brings Efficient Training for Large-scale Transformers

Rethinking the optimization process for self-supervised model-driven MRI reconstruction

DeepSpeed Data Efficiency: Improving Deep Learning Model Quality and Training Efficiency via Efficient Data Sampling and Routing

From WSI-level to Patch-level: Structure Prior Guided Binuclear Cell Fine-grained Detection

SelfCoLearn: Self-supervised collaborative learning for accelerating dynamic MR imaging

Pigeonhole Stochastic Gradient Langevin Dynamics for Large Crossed Mixed Effects Models

Iterative Data Refinement for Self-Supervised MR Image Reconstruction