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conftrace_

active learning

1,400 papers

AL

Papers

LABERT: A Combination of Local Aggregation and Self-Supervised Speech Representation Learning for Detecting Informative Hidden Units in Low-Resource ASR Systems Interspeech 2023 Learning functional sections in medical conversations: iterative pseudo-labeling and human-in-the-loop approach MLHC 2023 Learning Incoherent Light Emission Steering From Metasurfaces Using Generative Models WACV 2023 Learning When to Advise Human Decision Makers IJCAI 2023 Leveraging Importance Weights in Subset Selection ICLR 2023 LLMaAA: Making Large Language Models as Active Annotators EMNLP 2023 Local Context-Aware Active Domain Adaptation ICCV 2023 Maestro: A Gamified Platform for Teaching AI Robustness AAAI 2023 Making Your First Choice: To Address Cold Start Problem in Medical Active Learning MIDL 2023 Margin-based sampling in high dimensions: When being active is less efficient than staying passive ICML 2023 MCAL: Minimum Cost Human-Machine Active Labeling ICLR 2023 MEAL: Stable and Active Learning for Few-Shot Prompting EMNLP 2023 Memory-Based Dual Gaussian Processes for Sequential Learning ICML 2023 MHPL: Minimum Happy Points Learning for Active Source Free Domain Adaptation CVPR 2023 Models Teaching Models: Improving Model Accuracy with Slingshot Learning EACL 2023 Multi-Classifier Adversarial Optimization for Active Learning AAAI 2023 Multi-Objective GFlowNets ICML 2023 Multitask Learning with No Regret: from Improved Confidence Bounds to Active Learning NeurIPS 2023 Multi-View Active Fine-Grained Visual Recognition ICCV 2023 Navigating the Pitfalls of Active Learning Evaluation: A Systematic Framework for Meaningful Performance Assessment NeurIPS 2023 Neural Machine Translation through Active Learning on low-resource languages: The case of Spanish to Mapudungun ACL 2023 NewsPanda: Media Monitoring for Timely Conservation Action AAAI 2023 No Change, No Gain: Empowering Graph Neural Networks with Expected Model Change Maximization for Active Learning NeurIPS 2023 Nonparametric Indirect Active Learning AISTATS 2023 Non-Programmers Can Label Programs Indirectly via Active Examples: A Case Study with Text-to-SQL EMNLP 2023