5 papers
Veo-Act: How Far Can Frontier Video Models Advance Generalizable Robot Manipulation?
Zhongru Zhang, Chenghan Yang, Qingzhou Lu +4
Video generation models have advanced rapidly and are beginning to show a strong understanding of physical dynamics. In this paper, we investigate how far an advanced video generat…
Diffusion Policy with Bayesian Expert Selection for Active Multi-Target Tracking
Haotian Xiang, Qin Lu, Yaakov Bar-Shalom
Active multi-target tracking requires a mobile robot to balance exploration for undetected targets with exploitation of uncertain tracked ones. Diffusion policies have emerged as a…
Scalable Variational Bayesian Fine-Tuning of LLMs via Orthogonalized Low-Rank Adapters
Haotian Xiang, Bingcong Li, Qin Lu
When deploying large language models (LLMs) to safety-critical applications, uncertainty quantification (UQ) is of utmost importance to self-assess the reliability of the LLM-based…
Conformalized Gaussian processes for online uncertainty quantification over graphs
Jinwen Xu, Qin Lu, Georgios B. Giannakis
Uncertainty quantification (UQ) over graphs arises in a number of safety-critical applications in network science. The Gaussian process (GP), as a classical Bayesian framework for…
Fine-tuning LLMs with variational Bayesian last layer for high-dimensional Bayesian optimization
Haotian Xiang, Jinwen Xu, Qin Lu
A plethora of applications entail solving black-box optimization problems with high evaluation costs, including drug discovery, material design, as well as hyperparameter tuning. T…