15 citations · 15 across the 5 of their papers we have counts for
5 papers
FAIR-Calib: Frontier-Aware Instability-Reweighted Calibration for Post-Training Quantization of Diffusion Large Language Models
Haoyu Huang, Linlin Yang, Sheng Xu +5
Diffusion Large Language Models (dLLMs) refine tokens iteratively but commit them irreversibly, leading to a "stability lag" where early decisions remain fragile even after being w…
LDFE: Laplacian Decoupled Feature Enhancement Block for Dual-Stream CNN-based RGB-IR Object Detection
Wenhao Dong, Xiaoyan Luo, Linlin Yang +4
The complementary information between RGB and IR images can significantly enhance object detection performance under extreme conditions. Existing methods prefer dual-stream CNN bac…
Circuit-Inspired High-Order Neural Networks with Unified Neural Dynamics Modeling for PDE Solving and Visual Perception
Tongfei Chen, Jingying Yang, Linlin Yang +8
Deep networks often rely on architectural heuristics to shape representation evolution, limiting their ability to model data governed by intrinsic dynamics. We present the Circuit-…
Graph Structure Refinement with Energy-based Contrastive Learning
Xianlin Zeng, Yufeng Wang, Yuqi Sun +3
Graph Neural Networks (GNNs) have recently gained widespread attention as a successful tool for analyzing graph-structured data. However, imperfect graph structure with noisy links…
Fusion-Mamba for Cross-modality Object Detection
Wenhao Dong, Haodong Zhu, Shaohui Lin +6
Cross-modality fusing complementary information from different modalities effectively improves object detection performance, making it more useful and robust for a wider range of a…