2 citations · 2 across the 5 of their papers we have counts for
6 papers
Bayesian optimization with kernel ensembles and disagreement-based acquisition for source localization and acoustic inversion
Heng Zhang, Haotian Xiang, Florian Meyer +1
Joint source localization and geoacoustic inversion requires optimizing an objective built from an expensive normal mode propagation model. Bayesian optimization (BO) with a Gaussi…
Enhancing Bayesian Optimization and Active Learning Through Kernel Diversity
Heng Zhang, Haotian Xiang, Konstantinos D. Polyzos +2
Hyperparameter selection remains a key challenge in Bayesian optimization (BO) and Bayesian active learning (AL), as model misspecification can lead to suboptimal performance, whil…
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…
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…
Alignment and Safety in Large Language Models: Safety Mechanisms, Training Paradigms, and Emerging Challenges
Haoran Lu, Luyang Fang, Ruidong Zhang +47
Due to the remarkable capabilities and growing impact of large language models (LLMs), they have been deeply integrated into many aspects of society. Thus, ensuring their alignment…