6 papers
Linear Reusable Neural Bases Architecture for Network Compression
Binshuai Wang, Peng Wei, Mahyar Ghazanfari
Memory constraints remain a critical bottleneck in the deployment of large-scale AI models. Parameter sharing across network depth reduces model storage, but repeatedly applying an…
Language Generation as Optimal Control: Closed-Loop Diffusion in Latent Control Space
ZiYi Dong, Yuliang Huang, Weijian Deng +3
This work reformulates language generation as a stochastic optimal control problem, providing a unified theoretical perspective to analyze autoregressive and diffusion models and e…
Towards Automated Air Traffic Safety Assessment Around Non-Towered Airports Using Large Language Models
Torsten Darrell, Mahyar Ghazanfari, Jordan Kam +3
We investigate frameworks for post-flight safety analysis at non-towered airports using large language models (LLMs). Non-towered airports rely on the Common Traffic Advisory Frequ…
Neural Distance-Guided Path Integral Control for Tractor-Trailer Navigation
Peng Wei, Chen Peng, Stavros Vougioukas
Autonomous and safe navigation of tractor-trailer systems requires accurate, real-time collision avoidance and dynamically feasible control, particularly in cluttered and complex a…
Relative Wasserstein Angle and the Problem of the -Nearest Gaussian Distribution
Binshuai Wang, Peng Wei
Understanding the distributional structure of high-dimensional datasets has become an important topic, yet direct visual characterization is difficult. In this work, we develop a g…
Relative Translation Invariant Wasserstein Distance
Binshuai Wang, Qiwei Di, Ming Yin +3
Motivated by the Bures distance, we introduce a new family of distances, \emph{relative translation invariant Wasserstein distances}, denoted by , as an extension of the clas…