4 papers
MOGS: Monocular Object-guided Gaussian Splatting in Large Scenes
Shengkai Zhang, Yuhe Liu, Jianhua He +3
Recent advances in 3D Gaussian Splatting (3DGS) deliver striking photorealism, and extending it to large scenes opens new opportunities for semantic reasoning and prediction in app…
Parallel Layer Normalization for Universal Approximation
Yunhao Ni, Yuxin Guo, Yuhe Liu +4
This paper studies the approximation capabilities of neural networks that combine layer normalization (LN) with linear layers. We prove that networks consisting of two linear layer…
RLLaVA: An RL-central Framework for Language and Vision Assistants
Lei Zhao, Zihao Ma, Boyu Lin +3
We present an RL-central framework for Language and Vision Assistants (RLLaVA) with its formulation of Markov decision process (MDP). RLLaVA decouples RL algorithmic logic from mod…
SPEAR: Structured Pruning for Spiking Neural Networks via Synaptic Operation Estimation and Reinforcement Learning
Hui Xie, Yuhe Liu, Shaoqi Yang +6
While deep spiking neural networks (SNNs) demonstrate superior performance, their deployment on resource-constrained neuromorphic hardware still remains challenging. Network prunin…