3 papers
cs.CV2026
MetaMax: Improved Open-Set Deep Neural Networks via Weibull Calibration
Zongyao Lyu, Nolan B. Gutierrez, William J. Beksi
Open-set recognition refers to the problem in which classes that were not seen during training appear at inference time. This requires the ability to identify instances of novel cl…
cs.LG2026
Energy-Based Open-Set Active Learning for Object Classification
Zongyao Lyu, William J. Beksi
Active learning (AL) has emerged as a crucial methodology for minimizing labeling costs in deep learning by selecting the most valuable samples from a pool of unlabeled data for an…
cs.RO2026
ReconVLA: An Uncertainty-Guided and Failure-Aware Vision-Language-Action Framework for Robotic Control
Lingling Chen, Zongyao Lyu, William J. Beksi
Vision-language-action (VLA) models have emerged as generalist robotic controllers capable of mapping visual observations and natural language instructions to continuous action seq…