7 papers
Consistency Deep Equilibrium Models
Junchao Lin, Zenan Ling, Jingwen Xu +1
Deep Equilibrium Models (DEQs) have emerged as a powerful paradigm in deep learning, offering the ability to model infinite-depth networks with constant memory usage. However, DEQs…
Diving into Kronecker Adapters: Component Design Matters
Jiayu Bai, Danchen Yu, Zhenyu Liao +4
Kronecker adapters have emerged as a promising approach for fine-tuning large-scale models, enabling high-rank updates through tunable component structures. However, existing work…
A Large-Dimensional Analysis of ESPRIT DoA Estimation: Inconsistency and a Correction via RMT
Zhengyu Wang, Wei Yang, Xiaoyi Mai +3
In this paper, we perform asymptotic analyses of the widely used ESPRIT direction-of-arrival (DoA) estimator for large arrays, where the array size and the number of snapshots…
Radio-Frequency Inverse Rendering for Wireless Environment Modeling
Fuhai Wang, Zihan Jin, Lehang Wang +4
Neural rendering paradigms have recently emerged as powerful tools for radio frequency (RF). However, by entangling RF sources with scene geometry and material properties, existing…
Adaptive Discretization for Consistency Models
Jiayu Bai, Zhanbo Feng, Zhijie Deng +3
Consistency Models (CMs) have shown promise for efficient one-step generation. However, most existing CMs rely on manually designed discretization schemes, which can cause repeated…
IGNN-Solver: A Graph Neural Solver for Implicit Graph Neural Networks
Junchao Lin, Zenan Ling, Zhanbo Feng +6
Implicit graph neural networks (IGNNs), which exhibit strong expressive power with a single layer, have recently demonstrated remarkable performance in capturing long-range depende…