Summary of Deep Active Learning with Manifold-preserving Trajectory Sampling, by Yingrui Ji et al.
Deep Active Learning with Manifold-preserving Trajectory Samplingby Yingrui Ji, Vijaya Sindhoori Kaza, Nishanth Artham, Tianyang…
Deep Active Learning with Manifold-preserving Trajectory Samplingby Yingrui Ji, Vijaya Sindhoori Kaza, Nishanth Artham, Tianyang…
Dirichlet-Based Coarse-to-Fine Example Selection For Open-Set Annotationby Ye-Wen Wang, Chen-Chen Zong, Ming-Kun Xie, Sheng-Jun HuangFirst…
An incremental preference elicitation-based approach to learning potentially non-monotonic preferences in multi-criteria sortingby Zhuolin Li,…
Causal-Guided Active Learning for Debiasing Large Language Modelsby Li Du, Zhouhao Sun, Xiao Ding, Yixuan…
Avoid Wasted Annotation Costs in Open-set Active Learning with Pre-trained Vision-Language Modelby Jaehyuk Heo, Pilsung…
SS-ADA: A Semi-Supervised Active Domain Adaptation Framework for Semantic Segmentationby Weihao Yan, Yeqiang Qian, Yueyuan…
Automated Neural Patent Landscaping in the Small Data Regimeby Tisa Islam Erana, Mark A. FinlaysonFirst…
Parameter-Efficient Active Learning for Foundational modelsby Athmanarayanan Lakshmi Narayanan, Ranganath Krishnan, Amrutha Machireddy, Mahesh SubedarFirst…
Entity Alignment with Noisy Annotations from Large Language Modelsby Shengyuan Chen, Qinggang Zhang, Junnan Dong,…
AI-Guided Defect Detection Techniques to Model Single Crystal Diamond Growthby Rohan Reddy Mekala, Elias Garratt,…