Self-supervised fine-tuning refines the embedding space of a pretrained language encoder without labels. However, the commonly used approaches are computationally expensive. Specifically, contrastive learning-based methods need multiview data and in-batch negative examples, while negative-free approaches require auxili...
Kishor Kumar Bhaumik, Nícolas Roque dos Santos, Neil Shah et al.· 0 citations
Tensor methods have played a central role in analyzing multi-dimensional data across a wide range of real-world applications. At the same time, these methods provide low-rank representations, which enable trustworthy and parsimonious machine learning systems. However, even though they hold great promise, tensor methods...
Dawon Ahn, Yong-chan Park, Taehyung Kwon et al.· Proceedings of the 32nd ACM...· 0 citations
Large vision models provide useful representations for remote-sensing segmentation but are often too expensive for deployment at the satellite or field edge. Existing feature-level distillation methods also tend to assume similar teacher and student architectures and often stop feature alignment when task training begi...
Kishor Kumar Bhaumik, Nícolas Roque dos Santos, Jia Chen et al.· 0 citations
The results show that skill representation itself matters, and that simply preserving the structure already present in skill files can substantially improve retrieval.
Paimon Goulart, Liang Wu, Ke Wan et al.· 0 citations
This workshop aims to provide a forum for advancing tensor methods and applying them to various applications at the intersection of data mining and modern machine learning to foster an interactive environment for researchers to exchange ideas and build connections across communities.
Dawon Ahn, Yong-chan Park, Taehyung Kwon et al.· Proceedings of the 32nd ACM...· 0 citations
This work proposes a proof-of-concept pipeline that delivers on building an AI system that can ingest multi-modal data for railway crossings and provide safety assessment and scores that align with expert opinion and with safety scoring used by the Federal Railroad Administration.
Paimon Goulart, Chansong Lim, Nícolas Roque dos Santos et al.· 0 citations
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