label-efficient learning

Active Generalized Category Discovery with Diverse LLM Feedback EACL 2026 DiffECG: Diffusion Model-Powered Label-Efficient and Personalized Arrhythmia Diagnosis IJCAI 2025 Improving Task Diversity in Label Efficient Supervised Finetuning of LLMs EMNLP 2025 Instance-wise Supervision-level Optimization in Active Learning CVPR 2025 The Parables of the Mustard Seed and the Yeast: Extremely Low-Budget, High-Performance Nighttime Semantic Segmentation AAAI 2025 BiCAL: Bi-directional Contrastive Active Learning for Clinical Report Generation ACL 2024 Label-Efficient Few-Shot Semantic Segmentation with Unsupervised Meta-Training AAAI 2024 Label-efficient Semantic Scene Completion with Scribble Annotations IJCAI 2024 Masked Event Modeling: Self-Supervised Pretraining for Event Cameras WACV 2024 Revealing Hierarchical Structure of Leaf Venations in Plant Science via Label-Efficient Segmentation: Dataset and Method IJCAI 2024 Unified Domain Generalization and Adaptation for Multi-View 3D Object Detection NeurIPS 2024 ALAMBIC : Active Learning Automation Methods to Battle Inefficient Curation EACL 2023 LAVA: Label-Efficient Visual Learning and Adaptation WACV 2023 STARS: Spatial-Temporal Active Re-sampling for Label-Efficient Learning from Noisy Annotations AAAI 2023 GALAXY: Graph-based Active Learning at the Extreme ICML 2022 Label-Efficient Hybrid-Supervised Learning for Medical Image Segmentation AAAI 2022 Label-Efficient Semantic Segmentation with Diffusion Models ICLR 2022 LOG: Active Model Adaptation for Label-Efficient OOD Generalization NeurIPS 2022 Multidimensional Belief Quantification for Label-Efficient Meta-Learning CVPR 2022 GLoRIA: A Multimodal Global-Local Representation Learning Framework for Label-Efficient Medical Image Recognition ICCV 2021 LEAN-LIFE: A Label-Efficient Annotation Framework Towards Learning from Explanation ACL 2020 Multifaceted Uncertainty Estimation for Label-Efficient Deep Learning NeurIPS 2020 Regression with Comparisons: Escaping the Curse of Dimensionality with Ordinal Information JMLR 2020 TriggerNER: Learning with Entity Triggers as Explanations for Named Entity Recognition ACL 2020 Request-and-Reverify: Hierarchical Hypothesis Testing for Concept Drift Detection with Expensive Labels IJCAI 2018