1 citations · 1 across the 7 of their papers we have counts for
7 papers
PLS-Calib: A Partial Least Squares Framework for Event Camera and Odometry Calibration under Ground Motion Constraints
Guangyu Li, Xiao Li, Yujie Wu +5
Accurate extrinsic rotation calibration between sensors is fundamental to the performance of robotic perception systems. However, most existing calibration techniques rely on full…
Learning to Select, Not Relearn: Hard-Routed Mixtures of Reasoning LoRAs
Seyed Alireza Molavi, Zhan Su, Yan Hu +3
Composing independently trained LoRA adapters into a single large language model is useful for multi-domain adaptation, especially when the original training data cannot be shared.…
MMPG: MoE-based Adaptive Multi-Perspective Graph Fusion for Protein Representation Learning
Yusong Wang, Jialun Shen, Zhihao Wu +6
Graph Neural Networks (GNNs) have been widely adopted for Protein Representation Learning (PRL), as residue interaction networks can be naturally represented as graphs. Current GNN…
Tensorized Clustered LoRA Merging for Multi-Task Interference
Zhan Su, Fengran Mo, Guojun Liang +4
Despite the success of the monolithic dense paradigm of large language models (LLMs), the LoRA adapters offer an efficient solution by fine-tuning small task-specific modules and m…
Latent Space Score-based Diffusion Model for Probabilistic Multivariate Time Series Imputation
Guojun Liang, Najmeh Abiri, Atiye Sadat Hashemi +3
Accurate imputation is essential for the reliability and success of downstream tasks. Recently, diffusion models have attracted great attention in this field. However, these models…
Expected Grad-CAM: Towards gradient faithfulness
Vincenzo Buono, Peyman Sheikholharam Mashhadi, Mahmoud Rahat +2
Although input-gradients techniques have evolved to mitigate and tackle the challenges associated with gradients, modern gradient-weighted CAM approaches still rely on vanilla grad…
Higher-order Spatio-temporal Physics-incorporated Graph Neural Network for Multivariate Time Series Imputation
Guojun Liang, Prayag Tiwari, Slawomir Nowaczyk +1
Exploring the missing values is an essential but challenging issue due to the complex latent spatio-temporal correlation and dynamic nature of time series. Owing to the outstanding…