active learning

Optimal Sample Selection Through Uncertainty Estimation and Its Application in Deep Learning JMLR 2025 Page Stream Segmentation with LLMs: Challenges and Applications in Insurance Document Automation COLING 2025 Pangram at GenAI Detection Task 3: An Active Learning Approach to Machine-Generated Text Detection COLING 2025 Personalized Clustering via Targeted Representation Learning AAAI 2025 Preference Elicitation for Multi-objective Combinatorial Optimization with Active Learning and Maximum Likelihood Estimation IJCAI 2025 Probabilistic Factorial Experimental Design for Combinatorial Interventions ICML 2025 Provably Accurate Shapley Value Estimation via Leverage Score Sampling ICLR 2025 Quantifying and Narrowing the Unknown: Interactive Text-to-Video Retrieval via Uncertainty Minimization ICCV 2025 RAVEN++: Pinpointing Fine-Grained Violations in Advertisement Videos with Active Reinforcement Reasoning EMNLP 2025 Reinforcement Active Client Selection for Federated Heterogeneous Graph Learning AAAI 2025 Rethinking Epistemic and Aleatoric Uncertainty for Active Open-Set Annotation: An Energy-Based Approach CVPR 2025 Rethinking Full Finetuning from Pretraining Checkpoints in Active Learning for African Languages ACL 2025 Revisiting Active Learning under (Human) Label Variation EMNLP 2025 Sifting through the Haystack - Efficiently Finding Rare Animal Behaviors in Large-Scale Datasets WACV 2025 Structural-Entropy-Based Sample Selection for Efficient and Effective Learning ICLR 2025 SubLIME: Subset Selection via Rank Correlation Prediction for Data-Efficient LLM Evaluation ACL 2025 Supportive Negatives Spectral Augmentation for Source-Free Cross-Domain Segmentation AAAI 2025 The Parables of the Mustard Seed and the Yeast: Extremely Low-Budget, High-Performance Nighttime Semantic Segmentation AAAI 2025 The Power of LLM-Generated Synthetic Data for Stance Detection in Online Political Discussions ICLR 2025 To Label or Not to Label: Hybrid Active Learning for Neural Machine Translation COLING 2025 To Label or Not to Label: PALM - A Predictive Model for Evaluating Sample Efficiency in Active Learning Models ICCV 2025 Toward Fair and Accurate Cross-Domain Medical Image Segmentation: A VLM-Driven Active Domain Adaptation Paradigm ICCV 2025 Towards Regulatory-Confirmed Adaptive Clinical Trials: Machine Learning Opportunities and Solutions AISTATS 2025 UKBOB: One Billion MRI Labeled Masks for Generalizable 3D Medical Image Segmentation ICCV 2025 Uncertainty Awareness Enables Efficient Labeling for Cancer Subtyping in Digital Pathology WACV 2025