37 citations · 54 across the 21 of their papers we have counts for
5 papers · 1 filter
Parts-Mamba: Augmenting Joint Context with Part-Level Scanning for Occluded Human Skeleton
Tianyi Shen, Huijuan Xu, Nilesh Ahuja +3
Skeleton action recognition involves recognizing human action from human skeletons. The use of graph convolutional networks (GCNs) has driven major advances in this recognition tas…
Calibrated Decomposition of Aleatoric and Epistemic Uncertainty in Deep Features for Inference-Time Adaptation
Divake Kumar, Patrick Poggi, Sina Tayebati +3
Most estimators collapse all uncertainty modes into a single confidence score, preventing reliable reasoning about when to allocate more compute or adjust inference. We introduce U…
MoRA: Missing Modality Low-Rank Adaptation for Visual Recognition
Shu Zhao, Nilesh Ahuja, Tan Yu +2
Pre-trained vision language models have shown remarkable performance on visual recognition tasks, but they typically assume the availability of complete multimodal inputs during bo…
Windsock is Dancing: Adaptive Multimodal Retrieval-Augmented Generation
Shu Zhao, Tianyi Shen, Nilesh Ahuja +2
Multimodal Retrieval-Augmented Generation (MRAG) has emerged as a promising method to generate factual and up-to-date responses of Multimodal Large Language Models (MLLMs) by incor…
TS-OOD: Evaluating Time-Series Out-of-Distribution Detection and Prospective Directions for Progress
Onat Gungor, Amanda Sofie Rios, Nilesh Ahuja +1
Detecting out-of-distribution (OOD) data is a fundamental challenge in the deployment of machine learning models. From a security standpoint, this is particularly important because…