3 papers
cs.LG2025
Let the Void Be Void: Robust Open-Set Semi-Supervised Learning via Selective Non-Alignment
You Rim Choi, Subeom Park, Seojun Heo +2
Open-set semi-supervised learning (OSSL) leverages unlabeled data containing both in-distribution (ID) and unknown out-of-distribution (OOD) samples, aiming simultaneously to impro…
cs.CV2025
Accurate Scene Text Recognition with Efficient Model Scaling and Cloze Self-Distillation
Andrea Maracani, Savas Ozkan, Sijun Cho +6
Scaling architectures have been proven effective for improving Scene Text Recognition (STR), but the individual contribution of vision encoder and text decoder scaling remain under…
cs.LG2025
Guided Model Merging for Hybrid Data Learning: Leveraging Centralized Data to Refine Decentralized Models
Junyi Zhu, Ruicong Yao, Taha Ceritli +6
Current network training paradigms primarily focus on either centralized or decentralized data regimes. However, in practice, data availability often exhibits a hybrid nature, wher…