2 citations · 2 across the 9 of their papers we have counts for
10 papers
RATL: Learning from Retrieved Residuals for Robust Multivariate Time-Series Forecasting
Yuchen He, Yueyang Cang, Zhiyuan Ning +2
Retrieval-augmented generation (RAG) complements parametric models with retrieved external evidence. The same idea is attractive for continuous-output regression, but directly reus…
FeedbackTrack: Visual-Cortex-Inspired Cross-Frame Feedback for Transformer Tracking
Yueyang Cang, Xiaoteng Zhang, Zhiyuan Ning +2
Visual object tracking requires effective temporal integration, yet most Transformer trackers still rely on predominantly feed-forward feature extraction. Existing temporal mechani…
Structure-Guided Diffusion Model for EEG-Based Visual Cognition Reconstruction
Yongxiang Lian, Yueyang Cang, Pingge Hu +2
Objective: Decoding visual information from electroencephalography (EEG) is an important problem in neuroscience and brain-computer interface (BCI) research. Existing methods are l…
Intelligent Pathological Diagnosis of Gestational Trophoblastic Diseases via Visual-Language Deep Learning Model
Yuhang Liu, Yueyang Cang, Wenge Que +12
The pathological diagnosis of gestational trophoblastic disease(GTD) takes a long time, relies heavily on the experience of pathologists, and the consistency of initial diagnosis i…
Graph-GRPO: Stabilizing Multi-Agent Topology Learning via Group Relative Policy Optimization
Yueyang Cang, Xiaoteng Zhang, Erlu Zhao +7
Optimizing communication topology is fundamental to the efficiency and effectiveness of Large Language Model (LLM)-based Multi-Agent Systems (MAS). While recent approaches utilize…
The Role of Excitatory Parvalbumin-positive Neurons in the Tectofugal Pathway of Pigeon (Columba livia) Hierarchical Visual Processing
Shan Lu, Xiaoteng Zhang, Yueyang Cang +6
The visual systems of birds and mammals exhibit remarkable organizational similarities: the dorsal ventricular ridge (DVR) demonstrates a columnar microcircuitry that parallels the…
DINT Transformer
Yueyang Cang, Yuhang Liu, Xiaoteng Zhang +2
DIFF Transformer addresses the issue of irrelevant context interference by introducing a differential attention mechanism that enhances the robustness of local attention. However,…
Shared DIFF Transformer
Yueyang Cang, Yuhang Liu, Xiaoteng Zhang +2
DIFF Transformer improves attention allocation by enhancing focus on relevant context while suppressing noise. It introduces a differential attention mechanism that calculates the…
Can KAN Work? Exploring the Potential of Kolmogorov-Arnold Networks in Computer Vision
Yueyang Cang, Yu hang liu, Li Shi
Kolmogorov-Arnold Networks(KANs), as a theoretically efficient neural network architecture, have garnered attention for their potential in capturing complex patterns. However, thei…
RetCompletion:High-Speed Inference Image Completion with Retentive Network
Yueyang Cang, Pingge Hu, Xiaoteng Zhang +3
Time cost is a major challenge in achieving high-quality pluralistic image completion. Recently, the Retentive Network (RetNet) in natural language processing offers a novel approa…