2 citations · 11 across the 29 of their papers we have counts for
32 papers
MotionCraft: Latent World Modeling with Sparse Attention for Visual Upscaling
Rong Fu, Chunlei Meng, Yangchen Zeng +9
Video super-resolution (VSR) aims to recover high-fidelity high-resolution videos from low-resolution inputs and is central to applications ranging from mobile capture to streaming…
Degeneracy-Guided List Compression for Greedy Graph Coloring
Rong Fu, Yongtai Liu, Xiaowen Ma +6
We study degeneracy guided list compression for greedy graph coloring when graph structure is available before colors are sampled. Our exposure calibrated ordering framework assign…
DynImmune-BERT: Dynamic Immune Repertoire Modeling with Neural ODE Driven Continuous Transformers
Rong Fu, Yongtai Liu, Xiaowen Ma +5
Longitudinal T cell receptor repertoires contain signals of clonal expansion, contraction, disappearance, and reappearance after immune perturbation. Static repertoire language mod…
SwiftGS: Episodic Priors for Immediate Satellite Surface Recovery
Rong Fu, Jiekai Wu, Xiaowen Ma +4
Rapid, large-scale 3D reconstruction from multi-date satellite imagery is vital for environmental monitoring, urban planning, and disaster response, yet remains difficult due to il…
SphUnc: Hyperspherical Uncertainty Decomposition and Causal Identification via Information Geometry
Rong Fu, Chunlei Meng, Jinshuo Liu +8
Reliable decision-making in complex multi-agent systems requires calibrated predictions and interpretable uncertainty. We introduce SphUnc, a unified framework combining hyperspher…
GaiaFlow: Semantic-Guided Diffusion Tuning for Carbon-Frugal Search
Rong Fu, Jia Yee Tan, Chunlei Meng +4
As the burgeoning power requirements of sophisticated neural architectures escalate, the information retrieval community has recognized ecological sustainability as a pivotal prior…
DAV-GSWT: Diffusion-Active-View Sampling for Data-Efficient Gaussian Splatting Wang Tiles
Rong Fu, Jiekai Wu, Yang Li +3
The emergence of 3D Gaussian Splatting has fundamentally redefined the capabilities of photorealistic neural rendering by enabling high-throughput synthesis of complex environments…
Chimera: Neuro-Symbolic Attention Primitives for Trustworthy Dataplane Intelligence
Rong Fu, Xiaowen Ma, Kun Liu +8
Deploying expressive learning models directly on programmable dataplanes promises line-rate, low-latency traffic analysis but remains hindered by strict hardware constraints and th…
VLM-Pruner: Buffering for Spatial Sparsity in an Efficient VLM Centrifugal Token Pruning Paradigm
Zhenkai Wu, Xiaowen Ma, Zhenliang Ni +4
Vision-language models (VLMs) excel at image understanding tasks, but the large number of visual tokens imposes significant computational costs, hindering deployment on mobile devi…
Ada-MoGE: Adaptive Mixture of Gaussian Expert Model for Time Series Forecasting
Zhenliang Ni, Xiaowen Ma, Zhenkai Wu +3
Multivariate time series forecasts are widely used, such as industrial, transportation and financial forecasts. However, the dominant frequencies in time series may shift with the…
Expert Merging: Model Merging with Unsupervised Expert Alignment and Importance-Guided Layer Chunking
Dengming Zhang, Xiaowen Ma, Zhenliang Ni +4
Model merging, which combines multiple domain-specialized experts into a single model, offers a practical path to endow Large Language Models (LLMs) and Multimodal Large Language M…
Spatial-Spectral Binarized Neural Network for Panchromatic and Multi-spectral Images Fusion
Yizhen Jiang, Mengting Ma, Anqi Zhu +3
Remote sensing pansharpening aims to reconstruct spatial-spectral properties during the fusion of panchromatic (PAN) images and low-resolution multi-spectral (LR-MS) images, finall…
TimeExpert: Boosting Long Time Series Forecasting with Temporal Mix of Experts
Xiaowen Ma, Shuning Ge, Fan Yang +5
Transformer-based architectures dominate time series modeling by enabling global attention over all timestamps, yet their rigid 'one-size-fits-all' context aggregation fails to add…
Cott-ADNet: Lightweight Real-Time Cotton Boll and Flower Detection Under Field Conditions
Rui-Feng Wang, Mingrui Xu, Matthew C Bauer +3
Cotton is one of the most important natural fiber crops worldwide, yet harvesting remains limited by labor-intensive manual picking, low efficiency, and yield losses from missing t…
Contrastive Prompt Clustering for Weakly Supervised Semantic Segmentation
Wangyu Wu, Zhenhong Chen, Xiaowen Ma +6
Weakly Supervised Semantic Segmentation (WSSS) with image-level labels has gained attention for its cost-effectiveness. Most existing methods emphasize inter-class separation, ofte…
Memory-R1: Enhancing Large Language Model Agents to Manage and Utilize Memories via Reinforcement Learning
Sikuan Yan, Xiufeng Yang, Zuchao Huang +10
Large Language Models (LLMs) have demonstrated impressive capabilities across a wide range of NLP tasks, but they remain fundamentally stateless, constrained by limited context win…
HVI-CIDNet+: Beyond Extreme Darkness for Low-Light Image Enhancement
Qingsen Yan, Kangbiao Shi, Yixu Feng +4
Low-Light Image Enhancement (LLIE) aims to restore vivid content and details from corrupted low-light images. However, existing standard RGB (sRGB) color space-based LLIE methods o…
Self-Evolving Multi-Agent Systems via Textual Backpropagation
Xiaowen Ma, Yunpu Ma, Chenyang Lin +6
Leveraging multiple Large Language Models (LLMs) has proven effective for addressing complex, high-dimensional tasks, but current approaches often rely on static, manually engineer…
TimePro: Efficient Multivariate Long-term Time Series Forecasting with Variable- and Time-Aware Hyper-state
Xiaowen Ma, Zhenliang Ni, Shuai Xiao +1
In long-term time series forecasting, different variables often influence the target variable over distinct time intervals, a challenge known as the multi-delay issue. Traditional…
Center-guided Classifier for Semantic Segmentation of Remote Sensing Images
Wei Zhang, Mengting Ma, Yizhen Jiang +4
Compared with natural images, remote sensing images (RSIs) have the unique characteristic. i.e., larger intraclass variance, which makes semantic segmentation for remote sensing im…
CD-Lamba: Boosting Remote Sensing Change Detection via a Cross-Temporal Locally Adaptive State Space Model
Zhenkai Wu, Xiaowen Ma, Rongrong Lian +4
Mamba, with its advantages of global perception and linear complexity, has been widely applied to identify changes of the target regions within the remote sensing (RS) images captu…
A Novel Scene Coupling Semantic Mask Network for Remote Sensing Image Segmentation
Xiaowen Ma, Rongrong Lian, Zhenkai Wu +8
As a common method in the field of computer vision, spatial attention mechanism has been widely used in semantic segmentation of remote sensing images due to its outstanding long-r…
STeInFormer: Spatial-Temporal Interaction Transformer Architecture for Remote Sensing Change Detection
Xiaowen Ma, Zhenkai Wu, Mengting Ma +4
Convolutional neural networks and attention mechanisms have greatly benefited remote sensing change detection (RSCD) because of their outstanding discriminative ability. Existent R…
TinyViM: Frequency Decoupling for Tiny Hybrid Vision Mamba
Xiaowen Ma, Zhenliang Ni, Xinghao Chen
Mamba has shown great potential for computer vision due to its linear complexity in modeling the global context with respect to the input length. However, existing lightweight Mamb…